Organising AI for safety: Identifying structural vulnerabilities to guide the design of AI-enhanced socio-technical systems
Gazos, A.; Kahn, J.; Kusche, I.; Büscher, C.; Götz, M.
2025. Safety Science, 184, 106731. doi:10.1016/j.ssci.2024.106731

Unveiling novel structural complexity of spiral carbon nanomaterials: Review on mechanical, thermal, and interfacial behaviors via molecular dynamics
Sharifian, A.; Fareghi, P.; Baghani, M.; Odegard, G. M.; van Duin, A. C. T.; Rajabpour, A.; Wu, J.; Baniassadi, M.
2025. Journal of Molecular Structure, 1321 (Part 1), Art.-Nr.: 139837. doi:10.1016/j.molstruc.2024.139837

Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing
Cappello, F.; Acosta, M.; Agullo, E.; Anzt, H.; Calhoun, J.; Di, S.; Giraud, L.; Grützmacher, T.; Jin, S.; Sano, K.; Sato, K.; Singh, A.; Tao, D.; Tian, J.; Ueno, T.; u. a.
2025. Future Generation Computer Systems, 163, Art.-Nr.: 107323. doi:10.1016/j.future.2024.05.022

Numerical solution of a parameter estimation problem arising in Prompt-Gamma Neutron Activation Analysis
Jesser, A.; Krycki, K.; Frank, M.
2024. Applied Mathematics in Science and Engineering, 32 (1), Article no: 2336170. doi:10.1080/27690911.2024.2336170

Optimization of AI Methods on Distributed-Memory Computing Architectures. Dissertation
Coquelin, D.
2024, Dezember 17. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000176552

Capturing the Variability of the Nocturnal Boundary Layer through Localized Perturbation Modeling
Kaiser, A.; Vercauteren, N.; Krumscheid, S.
2024. Journal of the Atmospheric Sciences. doi:10.1175/JAS-D-24-0036.1

Scalable Bayesian Inference of Large Simulations via Asynchronous Prefetching Multilevel Delayed Acceptance
Kruse, M.; Niu, Z.; Wolf, S.; Lykkegaard, M.; Bader, M.; Gabriel, A.-A.; Seelinger, L.
2024, Dezember 8. doi:10.5281/zenodo.14315614

Personalized federated learning for improving radar based precipitation nowcasting on heterogeneous areas
Sáinz-Pardo Díaz, J.; Castrillo, M.; Bartok, J.; Cachá, I. H.; Ondík, I. M.; Martynovskyi, I.; Alibabaei, K.; Berberi, L.; Kozlov, V.; López García, Á.
2024. Earth Science Informatics, 17 (6), 5561–5584. doi:10.1007/s12145-024-01438-9

Generating synthetic energy time series: A review
Turowski, M.; Heidrich, B.; Weingärtner, L.; Springer, L.; Phipps, K.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2024. Renewable and Sustainable Energy Reviews, 206, 114842. doi:10.1016/j.rser.2024.114842

Model driven data space exploration: Interoperable infrastructure for experimental and computational data
Kerzel, U.; Mathews, P.; Mouhib, F.-Z.; Siemer, N.; Kruzikova, P.; Hunke, S.; Ost, P.; Korte-Kerzel, S.; Hickel, T.
2024. Zenodo. doi:10.5281/zenodo.14184496

The EM Glossary: a community effort towards a harmonized terminology in electron microscopy
Brendike-Mannix, O.; Hofmann, V.; Pauly, C.; Kühbach, M.; Wollgarten, M.; Konijnenberg, P.; Schröder, R. R.; Aversa, R.; Brockhauser, S.; Özkan, Ö.; Azócar Guzmán, A.; Sedeqi, M. R.; Sandfeld, S.
2024, November 18. 3rd Helmholtz Metadata Collaboration Conference (2024), Online, 4.–6. November 2024. doi:10.5281/zenodo.14178185

A stochastic Galerkin lattice Boltzmann method for incompressible fluid flows with uncertainties
Zhong, M.; Xiao, T.; Krause, M. J.; Frank, M.; Simonis, S.
2024. Journal of Computational Physics, 517, 113344. doi:10.1016/j.jcp.2024.113344

A conditional deep learning model for super-resolution reconstruction of small-scale turbulent structures in particle-Laden flows
Tofighian, H.; Denev, J. A.; Kornev, N.
2024. Physics of Fluids, 36 (11), Art.-Nr.: 115173. doi:10.1063/5.0235192

Measurement of the polarizations of prompt and non-prompt J/ψ and ψ (2S) mesons produced in pp collisions at = 13 TeV
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2024. Physics Letters B, 858, Art.-Nr.: 139044. doi:10.1016/j.physletb.2024.139044

Carrier-phase direct numerical simulation and flamelet modeling of NO formation in a pulverized coal/ammonia co-firing flame
Wen, X.; Shamooni, A.; Zirwes, T.; Stein, O. T.; Kronenburg, A.; Hasse, C.
2024. Combustion and Flame, 269, 113722. doi:10.1016/j.combustflame.2024.113722

Evolution of SSH with OpenId Connect
Hardt, M.; Gudu, D.; Zachmann, G.; Brocke, L.
2024. Proceedings of International Symposium on Grids & Clouds (ISGC) 2024, Taiwan, 24th - 29th March 2024, Art.-Nr.: 23, Scuola Internazionale Superiore di Studi Avanzati (SISSA). doi:10.22323/1.458.0023

Multilingual Archaeology Benchmark Dataset for Ontology Matching
Kraus, F.
2024, Oktober 24. doi:10.5281/zenodo.12731599

DH Benchmark Dataset for Ontology Matching
Kraus, F.
2024, Oktober 24. doi:10.5281/zenodo.12731588

Base4NFDI Policy Paper: "Base4NFDI Services and EOSC: Guidance for Interoperability", Version 1
Bernard, L.; Jander, M.; Manske, A.; Miller, B.; Rettberg, N.; Ritter, X.; Rißler-Pipka, N.; Schäfer-Neth, C.; Stein, R.; Zänkert, S.
2024, Oktober 17. Zenodo. doi:10.5281/zenodo.13946300

Harnessing Orthogonality to Train Low-Rank Neural Networks
Coquelin, D.; Flügel, K.; Weiel, M.; Kiefer, N.; Debus, C.; Streit, A.; Götz, M.
2024. ECAI 2024 : 27th European Conference on Artificial Intelligence 19–24 October 2024, Santiago de Compostela, Spain Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024 ; Proceedings. Ed.: U. Endriss, 2106–2113, IOS Press. doi:10.3233/FAIA240729

Taylor Expansion in Neural Networks: How Higher Orders Yield Better Predictions
Zwerschke, P.; Weyrauch, A.; Götz, M.; Debus, C.
2024. ECAI 2024 – 27th European Conference on Artificial Intelligence, 19–24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024). Ed.: U. Endriss, 2983–2989, IOS Press. doi:10.3233/FAIA240838

A Gaia-X-based Ecosystem for Manufacturing: Lessons Learned from the Project Gaia-X4ICM
Erb, Y.; Teigeler, H.; Lins, S.; Sunyaev, A.; Gleich, K.; Behrendt, S.; Karimi, E.; Bott, A.; Lanza, G.; Schulze, V.; Fleischer, J.; Leander-Knoll, M.; Jaganathan, K.; Scheibenberger, K.; Frick, F.; u. a.
2024. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000174929

Account LInking SErvicE (ALISE)
Hardt, M.; Gudu, D.; Millar, P.; Zachmann, G.
2024, Oktober 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024

Updates on SSH with OpenId Connect
Gudu, D.; Zachmann, G.; Hardt, M.; Brocke, L.
2024, Oktober 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024

iMagine: Best practices for suppliers of image collections and analysis tools in aquatic sciences
Azmi, E.; Alibabaei, K.; Kozlov, V.; Lopez Garcia, A.; Schaap, D.; Sipos, G.
2024, Oktober 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024

Leveraging MLflow for Efficient Evaluation and Deployment of Large Language Models
Berberi, L.; Kozlov, V.; Alibabaei, K. F.; Esteban Sanchis, B.
2024, Oktober 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024

Templates for reproducible science
Esteban, B.; Laures, C.; Kozlov, V.; Hardt, M.
2024, Oktober 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024

Notify me: Updates about mytoken
Zachmann, G.; Hardt, M.
2024, Oktober 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024

Machine Learning Operations (MLOps): from global landscape to practice in AI4EOSC
Kozlov, V.; Berberi, L.; Esteban Sanchis, B.; Nguyen, G.; Díaz, J. S.-P.; Calatrava, A.; Moltó, G.; Tran, V.; García, Á. L.
2024, Oktober 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024

Flow characteristics at the interface during droplet formation in a flow-focusing microfluidic channel—numerical analysis of dripping and jetting regimes
Grigorov, E.; Denev, J. A.; Kirov, B.; Galabov, V.
2024. Acta Mechanica, 235 (10), 6057–6075. doi:10.1007/s00707-024-04031-9

K and Λ ( two-particle femtoscopic correlations in PbPb collisions at = 5.02 TeV
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2024. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 857, 138936. doi:10.1016/j.physletb.2024.138936

A Fully Parallelized and Budgeted Multilevel Monte Carlo Method and the Application to Acoustic Waves
Baumgarten, N.; Krumscheid, S.; Wieners, C.
2024. SIAM/ASA Journal on Uncertainty Quantification, 12 (3), 901–931. doi:10.1137/23M1588354

Framework for Curation and Distribution of Reference Datasets on the Example of Creep Data of Ni-Base Superalloys
Ávila, L. A. Calderón; Shakeel, Y.; Gedsun, A.; Forti, M.
2024, September 26. Materials Science and Engineering Congress (MSE 2024), Darmstadt, Deutschland, 24.–26. September 2024

Common Service Architecture for NFDI-MatWerk: Technical & Infrastructure Components Built for the MSE Community
Hunke, S.; Shakeel, Y.; Moghaddam, A.; Stotzka, R.
2024, September 26. Materials Science and Engineering Congress (MSE 2024), Darmstadt, Deutschland, 24.–26. September 2024

Materials Data Infrastructure and Ontology Development for Exemplary Reference Dataset
Gedsun, A.; Shakeel, Y.
2024, September 24. Materials Science and Engineering Congress (MSE 2024), Darmstadt, Deutschland, 24.–26. September 2024

Metadata schema and mapping service for FIB/SEM serial-sectioning and computed tomography
Pauly, C.; Joseph, R. E.; Vitali, E. G. G.; Aversa, R.; Stotzka, R.; Mücklich, F.; Engstler, M.; Hermann, H.-G.; Fell, J.
2024, September 24. Materials Science and Engineering Congress (MSE 2024), Darmstadt, Deutschland, 24.–26. September 2024

Integration of controlled vocabularies or ontologies in metadata schemas
Abdildina, G.; Aversa, R.; Jejkal, T.; Ost, P.-J.
2024, September 24. Materials Science and Engineering Congress (MSE 2024), Darmstadt, Deutschland, 24.–26. September 2024

Data Processing and Data Assimilation
Jha, V.
2024, September 12. KCDS Workshop on Data Processing and Data Assimilation (2024), Karlsruhe, Deutschland, 11.–12. September 2024

Metadata Management in practice using MatWerk tools
Chelbi, S.
2024, September 11. National Research Data Infrastructure for Materials Science and Engineering: NFDI-MatWerk Summer School (2024), Bremen, Deutschland, 10.–12. September 2024

The journey towards metadata management
Aversa, R.
2024, September 11. National Research Data Infrastructure for Materials Science and Engineering: NFDI-MatWerk Summer School (2024), Bremen, Deutschland, 10.–12. September 2024

Comparative Study of Federated Learning Frameworks NVFlare and Flower for Detecting Thermal Bridges in Urban Environments
Duda, L. J.; Alibabaei, K. F.; Vollmer, E.; Klug, L.; Benz, M.; Kozlov, V.; Rebekka Volk; Götz, M.; Schultmann, F.; Streit, A.
2024, September 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024

Numerical Simulation of Thermal Decomposition of Polyethylene with a Single-Particle Model
Zhang, F.; Cao, J.; Zirwes, T.; Netsch, N.; Tavakkol, S.; Zhang, R.; Bockhorn, H.; Stapf, D.
2024. Advances in Computational Heat and Mass Transfer – Proceedings of the 14th International Conference on Computational Heat and Mass Transfer (ICCHMT 2023), 4-8 September, 2023, Düsseldorf, Germany, Volume 1. Ed.: A. Benim, 180 – 191, Springer International Publishing. doi:10.1007/978-3-031-67241-5_17

Mechanism of activation and autophosphorylation of a histidine kinase
Kansari, M.; Idiris, F.; Szurmant, H.; Kubař, T.; Schug, A.
2024. Communications Chemistry, 7 (1), Art.-Nr.: 196. doi:10.1038/s42004-024-01272-6

Emotion Regulation in Obsessive-Compulsive Disorder: An Ecological Momentary Assessment Study
Bischof, C.; Hohensee, N.; Dietel, F. A.; Doebler, P.; Klein, N.; Buhlmann, U.
2024. Behavior Therapy, 55 (5), 935–949. doi:10.1016/j.beth.2024.01.011

Assessing the potential of free-tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events
Schneider, M.; Toride, K.; Khosrawi, F.; Hase, F.; Ertl, B.; Diekmann, C. J.; Yoshimura, K.
2024. Atmospheric Measurement Techniques, 17 (17), 5243–5259. doi:10.5194/amt-17-5243-2024

Multi-Objective Optimization for Multi-Agent Injection Strategies in Subsurface CO2 Storage
Pettersson, P.; Krumscheid, S.; Gasda, S.
2024. Conference Proceedings, ECMOR 2024, 1–14, European Association of Geoscientists and Engineers (EAGE). doi:10.3997/2214-4609.202437062

Webinar on Studies in Europe
Jha, V.
2024, August 31. Webinar on Studies in Europe (2024), Bengaluru, Indien, 30.–31. August 2024

base-repo v1.5.5
Jejkal, T.; Hartmann, V.
2024, August 29. doi:10.5281/zenodo.7660035

mapping-service
Inckmann, M.; Jejkal, T.; Hartmann, V.; Pfeil, A.
2024, August 27. doi:10.5281/zenodo.13378984

Research Ideas to Patents: A Walkthrough
Jha, V.
2024, August 22. Intercollegiate Faculty Development Program (2024), Bengaluru, Indien, 19.–23. August 2024

IUC04: Towards semi automated construction of Defect Phase Diagrams
Rejiba, K.; Mathews, P.; Siemer, N.; Kerzel, U.; Kruzikova, P.; Saikia, U.; Philipp, O.; Korte-Kerzel, S.; Hickel, T.
2024. Zenodo. doi:10.5281/zenodo.13220179

The role of thermodiffusion and dimensionality in the formation of cellular instabilities in hydrogen flames
Zirwes, T.; Zhang, F.; Kaiser, T. L.; Oberleithner, K.; Stein, O. T.; Bockhorn, H.; Kronenburg, A.
2024. Proceedings of the Combustion Institute, 40 (1-4), Art.-Nr.: 105665. doi:10.1016/j.proci.2024.105665

Evidence for tWZ production in proton-proton collisions at = 13 TeV in multilepton final states
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2024. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 855, Art.-Nr.: 138815. doi:10.1016/j.physletb.2024.138815

NFDI-MatWerk/IUC02 Data schema for creep data of Ni-based superalloys including a comprehensive documentation of test results and metadata
Ávila Calderón, L. A.; Alexander, L.; Shakeel, Y.; Schriever, S.; Gedsun, A.; Forti, M.; Jordan, H.; Han, Y.; Baer, O.; Aversa, R.; Olbricht, J.; Hammerschmidt, T.; Hickel, T.; Skrotzki, B.
2024. Zenodo. doi:10.5281/zenodo.11668376

From method development to software integration: A comprehensive approach to geostatistical variogram uncertainty. Dissertation
Mälicke, M.
2024, Juli 12. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000172259

FAIR Data Commons Application Use Cases
Chelbi, S.; Jejkal, T.
2024, Juli 4. Helmholtz Metadata Collaboration Summer Meeting (HMC 2024), Kiel, Deutschland, 2.–5. Juli 2024

Easy Creation of Controlled Vocabularies Using EVOKS
Abdildina, G.; Aversa, R.; Kraus, F.; Ost, P.; Chelbi, S.; Jejkal, T.; Stotzka, R.; Blumenröhr, N.; Frank, L.; Götzelmann, G.; Hartmann, V.; Jha, V.; Pfeil, A.; Shakeel, Y.; Tögel, P.; u. a.
2024, Juli 3. Helmholtz Metadata Collaboration Summer Meeting (HMC 2024), Kiel, Deutschland, 2.–5. Juli 2024

Divergent Associations of Slow‐Wave Sleep versus Rapid Eye Movement Sleep with Plasma Amyloid‐Beta
Rosenblum, Y.; Pereira, M.; Stange, O.; Weber, F. D.; Bovy, L.; Tzioridou, S.; Lancini, E.; Neville, D. A.; Klein, N.; de Wolff, T.; Stritzke, M.; Kersten, I.; Uhr, M.; Claassen, J. A. H. R.; Steiger, A.; u. a.
2024. Annals of Neurology, 96 (1), 46–60. doi:10.1002/ana.26935

Structure and Dynamics of Hexagonal Cells in H/CO Flames
Zirwes, T.; Eckart, S.; Zhang, F.; Kaiser, T. L.; Oberleithner, K.; Stein, O. T.; Bockhorn, H.; Kronenburg, A.
2024, Juli. 40th International Symposium "Emphazing Energy Transition" (CI’S 2024), Mailand, Italien, 21.–26. Juli 2024

The role of thermodiffusion and dimensionality in the formation of cellular instabilities in hydrogen flames
Zirwes, T.; Zhang, F.; Kaiser, T. L.; Oberleithner, K.; Stein, O. T.; Bockhorn, H.; Kronenburg, A.
2024, Juli. 40th International Symposium "Emphazing Energy Transition" (CI’S 2024), Mailand, Italien, 21.–26. Juli 2024

Search for high-mass exclusive diphoton production with tagged protons in proton-proton collisions at √s = 13 TeV
CMS Collaboration; TOTEM Collaboration; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; u. a.
2024. Physical Review D, 110 (1), Art.-Nr.: 012010. doi:10.1103/PhysRevD.110.012010

Scalable multiscale-spectral GFEM with an application to composite aero-structures
Bénézech, J.; Seelinger, L.; Bastian, P.; Butler, R.; Dodwell, T.; Ma, C.; Scheichl, R.
2024. Journal of Computational Physics, 508, Art.-Nr.: 113013. doi:10.1016/j.jcp.2024.113013

ReCycle: Fast and Efficient Long Time Series Forecasting with Residual Cyclic Transformers
Weyrauch, A.; Steens, T.; Taubert, O.; Hanke, B.; Eqbal, A.; Götz, E.; Streit, A.; Götz, M.; Debus, C.
2024. 2024 IEEE Conference on Artificial Intelligence (CAI), Singapore, Singapore, 25-27 June 2024, 1187–1194, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CAI59869.2024.00212

Making Federated Learning Accessible to Scientists: The AI4EOSC Approach
Sáinz-Pardo Díaz, J.; Heredia Canales, A.; Heredia Cachá, I.; Tran, V.; Nguyen, G.; Alibabaei, K.; Obregón Ruiz, M.; Rebolledo Ruiz, S.; López García, Á.
2024. IH&MMSec ’24: Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security, 253 – 264, Association for Computing Machinery (ACM). doi:10.1145/3658664.3659642

NFFA-Europe Pilot - D9.3 - Integration of the second set of the VA offer
Aversa, R.; Blumenröhr, N.; Vitali, E. G. G.; Recchia, A.
2024, Juni 19. Zenodo. doi:10.5281/zenodo.12168771

Bring FAIR DOs into Light
Jejkal, T.
2024. Zenodo. doi:10.5281/zenodo.11918940

A Lightweight Introduction to FAIR Digital Objects
Blumenröhr, N.
2024, Juni 14. NEP Summer School on Data Management and Virtual Access (2024), Iraklio, Griechenland, 12.–14. Juni 2024

How to Manage Metadata : The MetaRepo: Introduction
Jejkal, T.
2024, Juni 13. NEP Summer School on Data Management and Virtual Access (2024), Iraklio, Griechenland, 12.–14. Juni 2024

Research data usecase: Scanning Electron Microscopy
Aversa, R.
2024, Juni 13. NEP Summer School on Data Management and Virtual Access (2024), Iraklio, Griechenland, 12.–14. Juni 2024

How to describe data: Metadata Schemas
Aversa, R.
2024, Juni 13. NEP Summer School on Data Management and Virtual Access (2024), Iraklio, Griechenland, 12.–14. Juni 2024

How Does Feature Engineering Impact UAV-based Multispectral Semantic Segmentation? An RGB and Thermal Image Ablation Study
Vollmer, E.; Benz, M.; Kahn, J.; Klug, L.; Volk, R.; Schultmann, F.; Götz, M.
2024, Juni 12. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024

Drift Monitoring as Service for MLOps
Esteban Sanchis, B.; Grover, H.; Kozlov, V.; Mosaku, A.
2024, Juni 12. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024

Introduction to FAIR Principles
Aversa, R.
2024, Juni 12. NEP Summer School on Data Management and Virtual Access (2024), Iraklio, Griechenland, 12.–14. Juni 2024

NEP Summer School on Data Management and Virtual Access: basics and motivations
Aversa, R.
2024, Juni 12. NEP Summer School on Data Management and Virtual Access (2024), Iraklio, Griechenland, 12.–14. Juni 2024

iMagine: Empowering Aquatic Research through AI-Driven Tools for Imaging Data Analysis
Azmi, E.; Alibabaei, K.; Kozlov, V.; García, Á. L.; Schaap, D.; Sipos, G.
2024, Juni 12. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024

Investigating Data Distribution Variability Across Devices in Federated Learning: Comparative Analysis of Algorithm Performance
Duda, L.; Alibabaei, K.; Berberi, L.; Kozlov, V.; Streit, A.
2024, Juni 12. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024

Federated Learning for Urban Energy Efficiency: Detecting Thermal with UAV-based Imaging and AI
Duda, L. J.; Alibabaei, K.; Vollmer, E.; Klug, L.; Benz, M.; Kozlov, V.; Volk, R.; Goetz, M.; Schultmann, F.; Streit, A.
2024, Juni 12. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024

Ultra-high-granularity detector simulation with intra-event aware generative adversarial network and self-supervised relational reasoning
Hashemi, B.; Hartmann, N.; Sharifzadeh, S.; Kahn, J.; Kuhr, T.
2024. Nature Communications, 15 (1), Art.-Nr.: 4916. doi:10.1038/s41467-024-49104-4

Annotationen im Medienwandel
Ernst, F.; Götzelmann, G.; Hegel, P.; Kalchreuter, C.; Krewet, M.; Rapp, A.; Schenk, T.; Tonne, D.
2024. Logbuch Wissensgeschichte Abschlusspublikation SFB 980 Becker-Sawatzky, Mira / Wächter, Katrin / Wendt, Helge / Dadaş, Şirin / Eusterschulte, Anne / Hasselmann, Kristiane / James Johnston, Andrew / Quenstedt, Falk / Reufer, Claudia / Trauer, Hanna Zoe / Vogel, Christian, 421–438, Harrassowitz Verlag. doi:10.13173/9783447121804

Feasibility of Forecasting Highly Resolved Power Grid Frequency Utilizing Temporal Fusion Transformers
Pütz, S.; El Ashhab, H.; Hertel, M.; Mikut, R.; Götz, M.; Hagenmeyer, V.; Schäfer, B.
2024. e-Energy ’24: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 447–453, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661963

Turbulence closure in linearized analyses of non-uniform density flows
Kaiser, T. L.; Zirwes, T.; Zhang, F.; Oberleithner, K.
2024, Juni. ERCOFTAC SIG39 Symposium-Coherent Structures in Aeroacoustics (2024), Rom, Italien, 10.–12. Juni 2024

AI4EOSC : customizable AI platform in the EOSC context
Kozlov, V.; Alibabaei, K.; Berberi, L.; Esteban Sanchis, B.; Lopez Garcia, A.
2024, Juni. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024

A Probabilistic Model for Asynchronous Iterative Methods
Nayak, P.; Anzt, H.
2024. 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), San Francisco, CA, USA, 27-31 May 2024, 260–269, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPSW63119.2024.00064

iMagine: A Cutting-Edge AI-Platform for Aquatic Sciences
Alibabaei, K.; Sipos, G.; Schaap, D.; López-García, A.; Kozlov, V.
2024, Mai 13. ISC High Performance (2024), Hamburg, Deutschland, 12.–16. Mai 2024

Untangling the Mysteries of Medieval Torah Scrolls
Frank, L.; Gotzelmann, G.; Tonne, D.
2024, Mai 2. Strategic Advisory Board (SAB) meeting for the Helmholtz Program EDF (2024), Karlsruhe, Deutschland, 2. Mai 2024

Simulation and Data Life Cycle Labs at SCC
Aversa, R.; Azmi, E.; Fischer, M.; Götz, M.
2024, Mai 2. Strategic Advisory Board (SAB) meeting for the Helmholtz Program EDF (2024), Karlsruhe, Deutschland, 2. Mai 2024

Longitudinal phase space density tomography constrained by the Vlasov-Fokker-Planck equation
Donoso, F.; Funkner, S.; Bründermann, E.; Reißig, M.; Santamaria Garcia, A.; Frank, M.; Müller, A. S.
2024, Mai. 15th International Particle Accelerator Conference (IPAC 2024), Nashville, TN, USA, 19.–24. Mai 2024

On the importance of turbulence modelling in a linear mean field analysis of turbulent flame configurations
Kaiser, T. L.; Zirwes, T.; Zhang, F.; Oberleithner, K.
2024, Mai. 19th International Conference on Numerical Combustion (ICNC 2024), Kyōto, Japan, 7.–10. Mai 2024

Simulation of plastic pyrolysis in fluidized bed
Zhang, F.; Tavakkol, S.; Zirwes, T.; Stapf, D.
2024, Mai. 24th International Symposium on Analytical and Applied Pyrolysis (Pyro 2024), Peking, China, 19.–23. Mai 2024

Longitudinal phase space density tomography constrained by the Vlasov-Fokker-Planck equation
Donoso, F.; Santamaria Garcia, A.; Mueller, A.-S.; Bruendermann, E.; Frank, M.; Reissig, M.; Funkner, S.
2024. 15th International Particle Accelerator Conference, Nashville, Tennessee : May 19-24, 2024, Nashville, Tennessee, USA : proceedings. Ed.: F. Pilat, 2350–2353, JACoW Publishing. doi:10.18429/JACoW-IPAC2024-WEPG55

iMagine, AI-supported imaging data and services for ocean and marine science
Sipos, G.; Schaap, D.; Lopez Garcia, A.; Kozlov, V.
2024. International Conference on Marine Data and Information Systems - Proceedings Volume. International Conference on Marine Data and Information Systems - Proceedings Volume., International Conference on Marine Data and Information Systems (IMDIS 2024 2024), Bergen, Norwegen, 27.05.2024–29.05.2024, 303–305

MatterMiners/tardis: 0.8.2
Giffels, M.; Fischer, M.; Haas, A.; Kroboth, S.; Schnepf, M.; Kuehn, E.; Schuhmacher, P.; Caspart, R.; von Cube, F.; Sammel, D.; Rottler, B.; Wienemann, P.; Kleinemühl, R.; Wozniewski, S.
2024, Mai. doi:10.5281/zenodo.11261058

Search for an exotic decay of the Higgs boson into a Z boson and a pseudoscalar particle in proton-proton collisions at √s = 13 TeV
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2024. Physics Letters B, 852, Art.-Nr.: 138582. doi:10.1016/j.physletb.2024.138582

Distributional Regression for Data Analysis
Klein, N.
2024. Annual Review of Statistics and Its Application, 11, 321–346. doi:10.1146/annurev-statistics-040722-053607

Basics of Federated Learning: Tips and Tricks
Alibabaei, K.
2024, April 22. AI4EOSC Webinar: Introduction to Federated Learning (2024), Online, 22.–23. April 2024

The EM Glossary: a community effort towards harmonized terminology in electron microscopy
Schröder, R.; Hofmann, V.; Kühbach, M.; Pauly, C.; Aversa, R.; Brockhauser, S.; Azócar Guzmán, A.; Joseph, R. E.; Özkan, Ö.; Konijnenberg, P. J.; Wollgarten, M.; Mannix-Brendike, O.; Sandfeld, S.
2024, April 19. Conference on Frontiers of Aberration Corrected Electron Microscopy (PICO 2024), Kasteel Vaalsbroek, Netherlands, 21.–25. April 2024. doi:10.5281/zenodo.11071439

Machine Learning from Evolution. Dissertation
Taubert, O.
2024, April 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000170101

A Cascadic Parareal Method for Parallel-in-Time Simulation of Compressible Supersonic Flow
Chen, Y.-C.; Nakajima, K.
2024. Journal of Information Processing, 32, 369 – 379. doi:10.2197/ipsjjip.32.369

Physics Informed Neural Networks for Neutron Transport in Large Sample Prompt Gamma Activation Analysis
Jesser, A.; Krycki, K.
2024, April 10. Mashine Learning Conference for X-Ray and Neutron-Based Experiments (2024), Garching bei München, Deutschland, 8.–10. April 2024

Bayesian Conditional Transformation Models
Carlan, M.; Kneib, T.; Klein, N.
2024. Journal of the American Statistical Association, 119 (546), 1360–1373. doi:10.1080/01621459.2023.2191820

Metadata Management in Correlative Characterization: Tales from the Metadata WG
Aversa, R.
2024, April 2. Frontiers in Correlative Material Characterization: Samples, Techniques, Instrumentation and Data Management (2024), Bad Honnef, 2.–5. April 2024

Bivariate Analysis of Birth Weight and Gestational Age by Bayesian Distributional Regression with Copulas
Rathjens, J.; Kolbe, A.; Hölzer, J.; Ickstadt, K.; Klein, N.
2024. Statistics in Biosciences, 16 (1), 290–317. doi:10.1007/s12561-023-09396-4

iMagine, AI-supported imaging data and services for ocean and marine science
Fava, I.; Lopez Garcia, A.; Schaap, D.; Krijer, T.; Sipos, G.; Kozlov, V.
2024, April. European Geosciences Union General Assembly (EGU 2024), Wien, Österreich, 14.–19. April 2024. doi:10.5194/egusphere-egu24-7635

Effects of Intrinsic Instabilities on the Response of Premixed Hydrogen/Air Conical Flames to Inlet Flow Perturbations
Yang, L.; Wang, Y.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2024. Flow, Turbulence and Combustion, 112 (4), 1275–1297. doi:10.1007/s10494-024-00535-5

Human judgement forecasting of COVID-19 in the UK
Bosse, N. I.; Abbott, S.; Bracher, J.; Leeuwen, E. van; Cori, A.; Funk, S.
2024. Wellcome Open Research, 8, Art.-Nr.: 416. doi:10.12688/wellcomeopenres.19380.2

Speedup of Hyperparameter Optimization in Propulate Using Approximative Surrogate Models. Bachelorarbeit
Dierksen, V.
2024, März 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000171813

Phase space density tomography constrained by the Vlasov-Fokker-Planck equation
Donoso, F.; Funker, S.; Bründermann, E.; Frank, M.; Müller, A.-S.
2024, März 18. 87. Jahrestagung der DPG und DPG-Frühjahrstagung der Sektion Kondensierte Materie (SKM 2024), Berlin, Deutschland, 17.–22. März 2024

Approximation and Optimization of Compute-Intensive Environmental Simulations through Machine Learning Methods. Dissertation
Azmi, E.
2024, März 5. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000169007

Flexible specification testing in quantile regression models
Kutzker, T.; Klein, N.; Wied, D.
2024. Scandinavian Journal of Statistics, 51 (1), 355–383. doi:10.1111/sjos.12671

Projektkurs für Mädels: Mit Mathe und KI reale Probleme lösen
Hofmann, S.; Schönbrodt, S.
2024. Mitteilungen der Deutschen Mathematiker-Vereinigung, 32 (2), 124–126. doi:10.1515/dmvm-2024-0037

Study of azimuthal anisotropy of ϒ(1S) mesons in pPb collisions at √NN = 8.16 TeV
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2024. Physics Letters B, 850, Art.-Nr.: 138518. doi:10.1016/j.physletb.2024.138518

OMI-based emission source classification in East China and its spatial redistribution in view of pollution control measures
Zara, M.; van der A, R.; Ding, J.; Stavrakou, T.; Boersma, F.
2024. Environmental Monitoring and Assessment, 196 (3), Art.-Nr.: 323. doi:10.1007/s10661-024-12421-8

Search for new Higgs bosons via same-sign top quark pair production in association with a jet in proton-proton collisions at = 13 TeV
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2024. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 850, Art.-Nr.: 138478. doi:10.1016/j.physletb.2024.138478

Measurements of azimuthal anisotropy of nonprompt D mesons in PbPb collisions at = 5.02 TeV
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2024. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 850, Art.-Nr.: 138389. doi:10.1016/j.physletb.2023.138389

AI4EOSC - D6.2 Intermediate status report about integration of pilot applications
Kozlov, V.; Sainz-Pardo, J.; Berberi, L.; Alibabaei, K.; Vollmer, E.; Błaszczak, M.; Krzyżanek, M.; Smok, J.; Bartok, J.; Sisan, P.; Papadopoulos, G.; Izquierdo, P.
2024. Zenodo. doi:10.5281/zenodo.10729327

Portable Mixed Precision Algebraic Multigrid on High Performance GPUs. Dissertation
Tsai, Y.-H.
2024, Februar 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000168914

Assessment of dynamic characteristics of fluidized beds via numerical simulations
Zhang, F.; Tavakkol, S.; Dercho, S.; Zhou, J.; Zirwes, T.; Zeller, M.; Vogt, J.; Zhang, R.; Bockhorn, H.; Stapf, D.
2024. Physics of Fluids, 36 (2), Art.-Nr.: 023348. doi:10.1063/5.0189519

Building the MDMC-NEP Glossary
Aversa, R.
2024, Februar 23. SIG Metadata and Ontologies Meeting (2024), Online, 23. Februar 2024

Metadata Management in Scientific Research: an overview
Aversa, R.
2024, Februar 22. 1st iENTRANCE@ENL Advanced School (2024), Rom, Italien, 20.–22. Februar 2024

The MDMC-NEP Glossary of Terms
Aversa, R.; Boubnov, A.; De Angelis, D.; Eschke, C.; Irvine, S.; Joseph, R. E.; Kabbe, M.; MacKinnon, N.; Irene, M.; Panighel, M.; Thelen, R.; Valentinis, D.
2024. Zenodo. doi:10.5281/zenodo.10663833

A Lightning Introduction to the NFDI4Ing Data Collections Explorer
Ost, P.
2024, Februar 15. TS4NFDI (2024), Online, 15. Februar 2024. doi:10.5445/IR/1000168463

Mapping Service
Jejkal, T.; Inckmann, M.; Hartmann, V.; Aversa, R.; Vitali, E. G. G.
2024, Februar 13

Essential parameters needed for a U-Net-based segmentation of individual bones on planning CT images in the head and neck region using limited datasets for radiotherapy application
Yawson, A. K.; Walter, A.; Wolf, N.; Klüter, S.; Hoegen, P.; Adeberg, S.; Debus, J.; Frank, M.; Jäkel, O.; Giske, K.
2024. Physics in Medicine & Biology, 69 (3), Art.-Nr.: 035008. doi:10.1088/1361-6560/ad1996

iMagine D3.2 Technical development roadmap for the AI image analysis use cases (update)
Alibabaei, K.; Kozlov, V.
2024, Februar 5. doi:10.5281/zenodo.10619470

MLflow Auth GUI (0.6.1)
Laures, C.; Esteban, B.; Berberi, L.; Kozlov, V.
2024, Februar. doi:10.5281/zenodo.10689888

cookiecutter-web | Version 1.0.0
Laures, C.; Esteban, B.; Kozlov, V.
2024, Februar. doi:10.5281/zenodo.10696463

Approximation method for fast calculation of transmission in multi-mode waveguides
Paszkiewicz, M.; Sukhova, M.; Dörfler, W.; Rockstuhl, C.
2024. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 41 (2), 174 – 184. doi:10.1364/JOSAA.504950

NFFA-Europe Pilot - D2.5 - First assessment of the data management procedures
De Giorgi, F.; Brandino, G. P.; Recchia, A.; Aversa, R.; Panighel, M.; Modolo, I.
2024, Januar 31. Zenodo. doi:10.5281/zenodo.10598472

KI und Prüfungen: Möglichkeiten und Herausforderungen aus rechtlicher Perspektive
Drossos, M.
2024. (Partnerschaft für innovative E-Prüfungen. Projektverbund der baden-württembergischen Universitäten (PePP), Hrsg.). doi:10.5445/IR/1000167081

BannMI deciphers potential n -to-1 information transduction in signaling pathways to unravel message of intrinsic apoptosis
Schmidt, B.; Sers, C.; Klein, N.
2024. (T. Lengauer, Hrsg.) Bioinformatics Advances, 4 (1), Article no: vbad175. doi:10.1093/bioadv/vbad175

Semi-Structured Distributional Regression
Rügamer, D.; Kolb, C.; Klein, N.
2024. The American Statistician, 78 (1), 88–99. doi:10.1080/00031305.2022.2164054

Quantifying the Impact of Regional-Scale Pressure Interference on Commercial CO2 Storage Targets for Multiple Licenses
Gasda, S.; Sandve, T. H.; Tveit, S.; Landa-Marban, D.; Pettersson, P.; Krumscheid, S.; Mykkeltvedt, T. S.; Dahle, H.
2024. SSRN Electronic Journal. doi:10.2139/ssrn.5053633

Resource-aware research on Universe and Matter: call-to-action in digital transformation
Bruers, B.; Cruces, M.; Demleitner, M.; Duckeck, G.; Düren, M.; Eich, N.; Enßlin, T.; Erdmann, J.; Erdmann, M.; Fackeldey, P.; Felder, C.; Fischer, B.; Fröse, S.; Funk, S.; Gasthuber, M.; u. a.
2024. The European Physical Journal Special Topics. doi:10.1140/epjs/s11734-024-01436-4

Vectorized Highly Parallel Density-based Clustering for Applications with Noise
Xavier, J. A.; Muriedas, J. P. G. H.; Nassyr, S.; Sedona, R.; Götz, M.; Streit, A.; Riedel, M.; Cavallaro, G.
2024. IEEE Access, 12, 181679–181692. doi:10.1109/ACCESS.2024.3507193

Truly Multivariate Structured Additive Distributional Regression
Kock, L.; Klein, N.
2024. Journal of Computational and Graphical Statistics, 1–17. doi:10.1080/10618600.2024.2434181

Observation of the decay
CMS Collaboration; Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Liko, D.; Mikulec, I.; u. a.
2024. The European Physical Journal C, 84 (10), Art.-Nr.: 1062. doi:10.1140/epjc/s10052-024-13114-9

Informed Spectral Normalized Gaussian Processes for Trajectory Prediction
Schlauch, C.; Wirth, C.; Klein, N.
2024. doi:10.5445/IR/1000175967

Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation
Yanez Sarmiento, P.; Witzke, S.; Klein, N.; Renard, B. Y.
2024. Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part IV, 336–351, Springer. doi:10.1007/978-3-031-70359-1_20

Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study
Mitra, P.; Schwalbe, G.; Klein, N.
2024. Proceedings of the IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 17th - 21st June 2024, Seattle, 3542–3552

Boosting distributional copula regression for bivariate time-to-event data
Sanchez, G. B.; Klein, N.; Groll, A.; Mayr, A.
2024. Proceedings of the 38th International Workshop on Statistical Modelling, 14th - 19th July, 2024, Durham, UK. Eds.: Jochen Einbeck, Reza Drikvandi, Georgios Karagiannis, Konstantinos Perrakis, Qing Zhang, 75–80

Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection
Kassem-Sbeyti, M.; Karg, M.; Wirth, C.; Klein, N.; Albayrak, S.
2024. Uncertainty in Artificial Intelligence, 1890–1900

Intergenerational Social Mobility in the United States: A Multivariate Analysis Using Distributional Regression
März, A.; Klein, N.; Kneib, T.; Mußhoff, O.
2024. Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science : Essays in Honour of Wolfgang Schmid. Ed.: S. Knoth, 295–335, Springer Nature Switzerland. doi:10.1007/978-3-031-69111-9_15

Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications
Stasinopoulos, M. D.; Kneib, T.; Klein, N.; Mayr, A.; Heller, G. Z.
2024. Cambridge University Press (CUP). doi:10.1017/9781009410076

tAKITA
Tonne, D.; Götzelmann, G.; Pütz, N.; Walz, M.; Schmidt, K. L.
2024. doi:10.5281/zenodo.13991887

Entwicklung einer Registry für typgebundene Operationen auf FAIR Digital Objects. Bachelorarbeit
Inckmann, M.
2024. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000174814

Reconstructing Particle Decay Trees with Quantum Graph Neural Networks for High Energy Physics
Strobl, M.; Kuehn, E.; Fischer, M.; Streit, A.
2024. 21st International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2022), Bari, I, October 23-28, 2022

Improving Noisy Hybrid Quantum Graph Neural Networks for Particle Decay Tree Reconstruction
Strobl, M.; Kuehn, E.; Fischer, M.; Streit, A.
2024. EPJ Web of Conferences, 295, Article no: 12004. doi:10.1051/epjconf/202429512004

Solving stationary nonlinear Fokker-Planck equations via sampling
Li, L.; Tang, Y.; Zhang, J.
2024. SIAM journal on applied mathematics

bamlss - Bayesian Additive Models for Location, Scale, and Shape (and Beyond)
Umlauf, N.; Klein, N.; Zeileis, A.
2024

EVOKS
Kraus, F.
2024. doi:10.5281/zenodo.13784194

Ginkgo - A math library designed to accelerate Exascale Computing Project science applications
Cojean, T.; Nayak, P.; Ribizel, T.; Beams, N.; Mike Tsai, Y.-H.; Koch, M.; Göbel, F.; Grützmacher, T.; Anzt, H.
2024. The International Journal of High Performance Computing Applications. doi:10.1177/10943420241268323

kit-data-manager/NEP_services: First Production Release
Blumenröhr, N.
2024. doi:10.5281/zenodo.13742141

Model Fusion via Neuron Transplantation
Öz, M.; Kiefer, N.; Debus, C.; Hörter, J.; Streit, A.; Götz, M.
2024. Machine Learning and Knowledge Discovery in Databases. Research Track : European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part IV. Ed. by Albert Bifet, Jesse Davis, Tomas Krilavičius, Meelis Kull, Eirini Ntoutsi, Indrė Žliobaitė, 3–19, Springer Nature Switzerland. doi:10.1007/978-3-031-70359-1_1

Democratizing Uncertainty Quantification
Seelinger, L.; Reinarz, A.; Lykkegaard, M. B.; Akers, R.; Alghamdi, A. M. A.; Aristoff, D.; Bangerth, W.; Bénézech, J.; Diez, M.; Frey, K.; Jakeman, J. D.; Jørgensen, J. S.; Kim, K.-T.; Martinelli, M.; Parno, M.; u. a.
2024. arxiv. doi:10.48550/arXiv.2402.13768

From Counting Stations to City-Wide Estimates: Data-Driven Bicycle Volume Extrapolation
Kaiser, S. K.; Klein, N.; Kaack, L. H.
2024. arxiv

Scalable Estimation for Structured Additive Distributional Regression
Umlauf, N.; Seiler, J.; Wetscher, M.; Simon, T.; Lang, S.; Klein, N.
2024. Journal of Computational and Graphical Statistics, 1–17. doi:10.1080/10618600.2024.2388604

Automatic heliostat learning for in situ concentrating solar power plant metrology with differentiable ray tracing
Pargmann, M.; Ebert, J.; Götz, M.; Maldonado Quinto, D.; Pitz-Paal, R.; Kesselheim, S.
2024. Nature Communications, 15 (1), Art.-Nr.: 6997. doi:10.1038/s41467-024-51019-z

@kit-data-manager/pid-component
Inckmann, M.
2024. doi:10.5281/zenodo.13629109

Wortvorschläge beim Chatten : KI und natürliche Sprachverarbeitung im Stochastikunterricht
Hofmann, S.; Frank, M.
2024. Mathematik lehren, (244), 24–29

Personalized Federated Learning for improving radar based precipitation nowcasting on heterogeneous areas
Díaz, J. S.-P.; Castrillo, M.; Bartok, J.; Cachá, I. H.; Ondík, I. M.; Martynovskyi, I.; Alibabaei, K.; Berberi, L.; Kozlov, V.; García, Á. L.
2024. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000173713

Carrier-phase direct numerical simulation and flamelet modeling of alkali metal emissions from pulverized biomass flames
Shamooni, A.; Wen, X.; Debiagi, P.; Stagni, A.; Gärtner, J. W.; Zirwes, T.; Stein, O. T.; Hasse, C.; Kronenburg, A.
2024. Proceedings of the Combustion Institute, 40 (1-4), 105309. doi:10.1016/j.proci.2024.105309

A Model for Centralized Management of Decentralized and Distributed Firewalls. Masterarbeit
Streib, J.
2024. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000173491

(Semi-) Automatic Review Process for Common Compound Characterization Data in Organic Synthesis
Huang, Y.-C.; Tremouilhac, P.; Kuhn, S.; Huang, P.-C.; Lin, C.-L.; Schlörer, N.; Taubert, O.; Götz, M.; Jung, N.; Bräse, S.
2024. ChemRxiv. doi:10.26434/chemrxiv-2024-1r9tb

Modeling and Quantifying Parameter Uncertainty of Co‐Seismic Non‐Classical Nonlinearity in Rocks
Niu, Z.; Gabriel, A.-A.; Seelinger, L.; Igel, H.
2024. Journal of Geophysical Research: Solid Earth, 129 (1). doi:10.1029/2023JB027149

Sequential Estimation Using Hierarchically Stratified Domains with Latin Hypercube Sampling
Krumscheid, S.; Pettersson, P.
2024. Monte Carlo and Quasi-Monte Carlo Methods : MCQMC 2022, Linz, Austria, July 17–22. Ed.: A. Hinrichs, 393–411, Springer International Publishing. doi:10.1007/978-3-031-59762-6_19

Surrogate Modelling for Core Degradation in pressurized Water Reactors
Dressner, J.; Götz, M.; Stakhanova, A.; Gabrielli, F.; Debus, C.
2024. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024

Efficient interface to the GridKa tape storage system
Musheghyan, H.; Petzold, A.; Ressmann, D.; Konstantinov, P.; Lobontu, D.-D.; Gottmann, A.; Ambroj Pérez, S.; Mol, X.
2024. (R. De Vita, X. Espinal, P. Laycock & O. Shadura, Hrsg.) EPJ Web of Conferences, 295, Art.-Nr.: 01020. doi:10.1051/epjconf/202429501020

CPU Performance Study for HEP Workloads with Respect to the Number of Single-core Slots
Schnepf, M. J.; Fischer, M.; Petzold, A.
2024. (R. De Vita, X. Espinal, P. Laycock & O. Shadura, Hrsg.) EPJ Web of Conferences, 295, Art.-Nr.: 07010. doi:10.1051/epjconf/202429507010

D2.7 : Second assessment of access provision
Fonseca, L.; Colpo, P.; Ekinci, Y.; Kazazis, D.; Maximov, I.; Obradors, X.; Frontera, C.; Aversa, R.; Anson, S.; Stratakis, E.; Kavatzikidou, E.; Klini, A.; Piccinin, S.; Orani, D.
2024. doi:10.5281/zenodo.12700914

Structure and dynamics of hexagonal cells in H/CO flames
Zirwes, T.; Eckart, S.; Zhang, F.; Kaiser, T. L.; Oberleithner, K.; Stein, O. T.; Bockhorn, H.; Kronenburg, A.
2024. Proceedings of the Combustion Institute, 40 (1-4), 105332. doi:10.1016/j.proci.2024.105332

Treuhandstelle für Mobilitätsdaten TreuMoDa : Abschlussbericht zum Teilvorhaben des Karlsruher Instituts für Technologie
Czech, A.; Geenen, V.; Krauß, P.; Lee, J.; Riedel, T.; Winandi, A.
2024. doi:10.5445/IR/1000172026

Treuhandstelle für Mobilitätsdaten TreuMoDa
Czech, A.; Geenen, V.; Krauß, P.; Lee, J.; Riedel, T.; Winandi, A.
2024. doi:10.5445/IR/1000172019

ICON release 2024.01
ICON partnership (DWD, MPI-M, DKRZ, KIT, C2SM)
2024. doi:10.35089/WDCC/IconRelease01

Towards a platform-portable linear algebra backend for OpenFOAM
Olenik, G.; Koch, M.; Boutanios, Z.; Anzt, H.
2024. Meccanica. doi:10.1007/s11012-024-01806-1

PETNet–Coincident Particle Event Detection using Spiking Neural Networks
Debus, J.; Debus, C.; Dissertori, G.; Götz, M.
2024. 2024 Neuro Inspired Computational Elements Conference (NICE), 9 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/NICE61972.2024.10549584

Earth Virtualization Engines (EVE)
Stevens, B.; Adami, S.; Ali, T.; Anzt, H.; Aslan, Z.; Attinger, S.; Bäck, J.; Baehr, J.; Bauer, P.; Bernier, N.; Bishop, B.; Bockelmann, H.; Bony, S.; Brasseur, G.; Bresch, D. N.; u. a.
2024. Earth System Science Data, 16 (4), 2113 – 2122. doi:10.5194/essd-16-2113-2024

Segmentation of 71 Anatomical Structures Necessary for the Evaluation of Guideline-Conforming Clinical Target Volumes in Head and Neck Cancers
Walter, A.; Hoegen-Saßmannshausen, P.; Stanic, G.; Rodrigues, J. P.; Adeberg, S.; Jäkel, O.; Frank, M.; Giske, K.
2024. Cancers, 16 (2), Art.-Nr.: 415. doi:10.3390/cancers16020415

Sensitivity of the polar boundary layer to transient phenomena
Kaiser, A.; Vercauteren, N.; Krumscheid, S.
2024. Nonlinear Processes in Geophysics, 31 (1), 45–60. doi:10.5194/npg-31-45-2024

Discovering Process Dynamics for Scalable Perovskite Solar Cell Manufacturing with Explainable AI
Klein, L.; Ziegler, S.; Laufer, F.; Debus, C.; Götz, M.; Maier-Hein, K.; Paetzold, U. W.; Isensee, F.; Jäger, P. F.
2024. Advanced Materials, 36 (7), Art.-Nr.: 2307160. doi:10.1002/adma.202307160

GPU-resident sparse direct linear solvers for alternating current optimal power flow analysis
Świrydowicz, K.; Koukpaizan, N.; Ribizel, T.; Göbel, F.; Abhyankar, S.; Anzt, H.; Peleš, S.
2024. International Journal of Electrical Power & Energy Systems, 155 (Part A), Art.-Nr.: 109517. doi:10.1016/j.ijepes.2023.109517

Correlation of wall heat loss with quenching distance for premixed H/Air flames during unsteady Flame-Wall interaction
Zhu, J.; Zirwes, T.; Zhang, F. C.; Li, Z. J.; Zhang, Y.; Pan, J. F.
2024. Chemical Engineering Science, 283, 119391. doi:10.1016/j.ces.2023.119391

Rigidity of -harmonic maps of low degree
Hörter, J.; Lamm, T.; Micallef, M.
2023. Annali della Scuola Normale Superiore di Pisa - Classe di Scienze, 24 (4), 2269 – 2310. doi:10.2422/2036-2145.202201_002

Computergestützte Analyse von Illustrationswiederverwendungen in deutschsprachigen Drucken des 16. Jahrhunderts. Am Beispiel Frankfurt am Main. Dissertation
Götzelmann, G.
2023, Dezember 21. doi:10.26083/tuprints-00026365

A parallel-in-time collocation method using diagonalization: theory and implementation for linear problems
Čaklović, G.; Speck, R.; Frank, M.
2023. Communications in Applied Mathematics and Computational Science, 18 (1), 55 – 85. doi:10.2140/camcos.2023.18.55

MatterMiners/tardis: 0.8.1
Giffels, M.; Fischer, M.; Haas, A.; Kroboth, S.; Schnepf, M.; Kuehn, E.; Schuhmacher, P.; Caspart, R.; Cube, F. von; Sammel, D.; Rottler, B.; Wienemann, P.; Kleinemühl, R.
2023, Dezember 20. doi:10.5281/zenodo.2240605

MetaStore v1.4.0
Hartmann, V.; Jejkal, T.; Chelbi, S.
2023, Dezember 19. doi:10.5281/zenodo.7814548

Specification of Turntable API for Metadata Repositories (Version 1.0.1)
Hartmann, V.; Heinrichs, B.
2023, Dezember 18. doi:10.5281/zenodo.10408707

Towards a Benchmark Dataset for the Digital Humanities
Ernst, F.; Blumenröhr, N.
2023. OM 2023 Ontology Matching : Proceedings of the 18th International Workshop on Ontology Matching, co-located with the 22nd International Semantic Web Conference (ISWC 2023), Athens, Greece, November 7, 2023. Ed.: P. Shvaiko, 200–202, CEUR-WS

dianagudu/webssh-oidc: v0.1.0
Gudu, D.
2023, Dezember 14. doi:10.5281/zenodo.10375454

dianagudu/ofcli: v0.6.3
Gudu, D.
2023, Dezember 14. doi:10.5281/zenodo.10375257

Measurement of Triple-Differential Z+Jet Cross Sections with the CMS Detector at 13 TeV and Modelling of Large-Scale Distributed Computing Systems. Dissertation
Horzela, M. M.
2023, Dezember 14. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000165566

Synchronization-free algorithms for exascale and beyond : A study of Asynchronous and Batched Iterative Methods. Dissertation
Nayak, P. V.
2023, Dezember 13. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000165437

mytoken-server 0.9.0
Zachmann, G.
2023, Dezember 5. doi:10.5281/zenodo.10260060

go-oidcfed 0.1.0
Zachmann, G.
2023, Dezember 5. doi:10.5281/zenodo.10259446

MatterMiners/tardis: 0.8.1
Giffels, M.; Fischer, M.; Haas, A.; Kroboth, S.; Schnepf, M.; Kuehn, E.; Schuhmacher, P.; Caspart, R.; Cube, F. von; Sammel, D.; Rottler, B.; Wienemann, P.; Kleinemühl, R.
2023, Dezember. doi:10.5281/zenodo.10411024

Three-precision algebraic multigrid on GPUs
Tsai, Y.-H. M.; Beams, N.; Anzt, H.
2023. Future Generation Computer Systems, 149, 280–293. doi:10.1016/j.future.2023.07.024

An Empirical Analysis of Newcomers’ Contributions to Software-Engineering Conferences
Alchokr, R.; Krüger, J.; Shakeel, Y.; Saake, G.; Leich, T.
2023. Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration – 25th International Conference on Asia-Pacific Digital Libraries, ICADL 2023, Taipei, Taiwan, December 4–7, 2023, Proceedings, Part I. Ed.: D. Goh, 231 – 247, Springer Nature Singapore. doi:10.1007/978-981-99-8085-7_21

Implementation of an InfraStructure for dAta-BasEd Learning in environmental sciences (ISABEL)
Strobl, M.; Azmi, E.; Bischof, B.; Dolich, A.; Hassler, S. K.; Mälicke, M.; Jaseetha, A. M.; Meyer, J.; Streit, A.; Zehe, E.
2023. E-Science-Tage 2023 : Empower Your Research – Preserve Your Data. Hrsg.: V. Heuveline, 295–300, heiBOOKS. doi:10.11588/heibooks.1288.c18091

Successful stories in NFFA-Europe Pilot and beyond
Aversa, R.
2023, November 29. iEntrance FAIR Data Day (2023), Bologna, Italien, 29. November 2023

Handling and Storing Metadata
Aversa, R.
2023, November 28. KNMFi User Meeting (2023), Ettlingen, Deutschland, 28.–29. November 2023

ParaDiag and Collocation Methods: Theory and Implementation. Dissertation
Caklovic, G.
2023, November 28. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000164518

NFFA-Europe Pilot - D16.4 - Report on additional data services
Aversa, R.; Blumenröhr, N.; Recchia, A.; Tsibidis, G.; Pantazis, Y.
2023, November 23. Zenodo. doi:10.5281/zenodo.10201227

Utilizing Reversibility of Quantum Gates for Quantum Knowledge Distillation
Wendenius, C.; Kuehn, E.; Heinkelein, M.; Streit, A.
2023, November 21. 7th Quantum Techniques in Machine Learning (QTML 2023), Genf, Schweiz, 19.–24. November 2023

QUAFEL: Quantum Framework Evaluation
Strobl, M.; Heinkelein, M.; Kuehn, E.; Wendenius, C.; Streit, A.
2023, November 21. 7th Quantum Techniques in Machine Learning (QTML 2023), Genf, Schweiz, 19.–24. November 2023

NFFA-Europe Pilot - D9.2 - Integration of the first VA services into the platform
Aversa, R.; Panighel, M.; Recchia, A.; Chiucconi, Y.; Brandino, G. P.; Tsibidis, G.; Pantazis, Y.; Sfakianakis, I.; Grassano, D.
2023, November 19. Zenodo. doi:10.5281/zenodo.10156330

AARC-G052 OAuth 2.0 Proxied Token Introspection (AARC-G052)
Hardt, M.; Bucik, D. F.; Jensen, J.; Kanakarakis, I.; Kanellopoulos, C.; Liampotis, N.; Salle, M.
2023. doi:10.5445/IR/1000172568

Porting Batched Iterative Solvers onto Intel GPUs with SYCL
Nguyen, P.; Nayak, P.; Anzt, H.
2023. Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, USA, 12-17 November 2023, 1048 – 1058, Association for Computing Machinery (ACM). doi:10.1145/3624062.3624181

Parallel Symbolic Cholesky Factorization
Ribizel, T.; Anzt, H.
2023. Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, USA, 12-17 November 2023, 1721 – 1727, Association for Computing Machinery (ACM). doi:10.1145/3624062.3624253

Semantic Segmentation of Crops and Weeds with Probabilistic Modeling and Uncertainty Quantification
Celikkan, E.; Saberioon, M.; Herold, M.; Klein, N.
2023. Proceedings of the IEEE/CVF International Conference on Computer Vision, Paris, 2nd - 6th October 2023, 582–592, IEEEXplore. doi:10.1109/ICCVW60793.2023.00065

KCDS How to prepare your application
Hühnerfuß, A.
2023. (U. Ehret, M. Frank & KIT-Zentrum MathSEE, Hrsg.)

Accounting for time dependency in meta‐analyses of concordance probability estimates
Schmid, M.; Friede, T.; Klein, N.; Weinhold, L.
2023. Research Synthesis Methods, 14 (6), 807–823. doi:10.1002/jrsm.1655

Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer
Holzschuh, J. C.; Mix, M.; Ruf, J.; Hölscher, T.; Kotzerke, J.; Vrachimis, A.; Doolan, P.; Ilhan, H.; Marinescu, I. M.; Spohn, S. K. B.; Fechter, T.; Kuhn, D.; Bronsert, P.; Gratzke, C.; Grosu, R.; u. a.
2023. Radiotherapy and Oncology, 188, Art.-Nr.: 109774. doi:10.1016/j.radonc.2023.109774

Deep-Learning-Based 3-D Surface Reconstruction—A Survey
Farshian, A.; Götz, M.; Cavallaro, G.; Debus, C.; Nießner, M.; Benediktsson, J. A.; Streit, A.
2023. Proceedings of the IEEE, 111 (11), 1464 – 1501. doi:10.1109/JPROC.2023.3321433

Novel Approach for Passive Mixing in Microfluidics Utilizing Porous PDMS Sponge
Grigorov, E.; Kirov, B.; Denev, J. A.; Galabov, V.
2023. 2023 International Scientific Conference on Computer Science (COMSCI), Sozopol, 18th-20th September 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/COMSCI59259.2023.10315880

Search for the Higgs boson decay to a pair of electrons in proton-proton collisions at = 13 TeV
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2023. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 846, Art.-Nr.: 137783. doi:10.1016/j.physletb.2023.137783

Improving volume-averaged simulations of matrix-stabilized combustion through direct X-ray µCT characterization: Application to NH₃/H₂-air combustion
Zirwes, T.; Vignat, G.; Toro, E. R.; Boigné, E.; Younes, K.; Trimis, D.; Ihme, M.
2023. Combustion and Flame, 257 (2), Article no: 113020. doi:10.1016/j.combustflame.2023.113020

Understanding Scalable Perovskite Solar Cell Manufacturing with Explainable AI
Klein, L.; Ziegler, S.; Laufer, F.; Debus, C.; Götz, M.; Maier-Hein, K.; Paetzold, U.; Isensee, F.; Jaeger, P.
2023

KiT-RT: An extendable framework for radiative transfer and therapy
Kusch, J.; Schotthöfer, S.; Stammer, P.; Wolters, J.; Xiao, T.
2023. ACM Transactions on Mathematical Software, 49 (4), Art.-Nr.: 38. doi:10.1145/3630001

A conceptual model for a FAIR DO fabric
Pfeil, A.
2023, Oktober 26. International Data Week : A Festival of Data / Plenary meeting (RDA 2023), Salzburg, Österreich, 23.–26. Oktober 2023

Metadata Required for FAIR Digital Objects
Stotzka, R.
2023, Oktober 23. International Data Week : A Festival of Data / Plenary meeting (RDA 2023), Salzburg, Österreich, 23.–26. Oktober 2023

Project 03: Mathematical Foundations of Bayesian Neural Networks
Debus, C.; Krumscheid, S.
2023. (U. Ehret, M. Frank & KIT-Zentrum MathSEE, Hrsg.)

Project 02: Advanced Parallelization Techniques for datadriven Uncertainty Quantification
Krumscheid, S.; Seelinger, L.
2023. (U. Ehret, M. Frank & KIT-Zentrum MathSEE, Hrsg.)

Project 04: Replacement of physical PSC simulation by machine learning in an Earth system model
Kirner, O.; Meyer, J.; Streit, A.
2023. (U. Ehret, M. Frank & KIT-Zentrum MathSEE, Hrsg.)

Designing a Mobility Data Trustee (MDT) – Findings From a Multi-Disciplinary Analysis of Requirements of an MDT
Czech, A.; Geenen, V.; Breß, C.; Turkovic Popovski, M.; Krauß, P.; Riedel, T.; Gauterin, F.
2023. Proceedings of the Conference on Research Data Infrastructure, 1, Article no: 64. doi:10.52825/cordi.v1i.370

Consensual videos of potentially re-identifiable individuals recorded at the Autonomous Driving Test Area Baden-Württemberg (raw images recorded daytime)
Geenen, V.; Riedel, T.
2023, Oktober 19. doi:10.5281/zenodo.10020644

Project 01: Scholars in the loop? Bridging the gap between distinctive knowledge of small disciplines and training data for AI
Götzelmann, G.; Tonne, D.; Debus, C.
2023. (U. Ehret, M. Frank & KIT-Zentrum MathSEE, Hrsg.)

Exploring storage technologies for HPSS disk caches
Petzold, A.
2023, Oktober 18. HEPiX Autumn Workshop (2023), Victoria, Kanada, 16.–20. Oktober 2023

Off-The-Shelf or Do It Yourself? Computer Vision Tools in Digital Humanities
Götzelmann, G.
2023

KCDS Virtual Open House 2023 - Fall
Kühn, E.; Chaichenets, L.
2023. (U. Ehret, M. Frank & KIT-Zentrum MathSEE, Hrsg.)

VπLES- hybrid vortex and grid based method for simulation of turbulent flows at high Re numbers
Kornev, N.; Darji, J.; Tofighian, H.; Denev, J. A.
2023. Proceedings of the 10th International Conference on Vortex Flow Mechanics (ICVFM 2023)

m-team-kit/alise: v1.0-zenodo
Hardt, M.; Millar, P.
2023, Oktober 13. doi:10.5281/zenodo.10262609

User-Oriented, Reusable Components and Tools for the Integration of FDOs into the Daily Research Routine
Jejkal, T.; Inckmann, M.; Kirar, A.
2023, Oktober 10. Helmholtz Metadata Collaboration Konferenz 2023 (HMC 2023), Online, 10.–12. Oktober 2023

Using EVOKS to build controlled vocabularies
Abdildina, G.; Ernst, F.; Aversa, R.; Ost, P.-J.
2023, Oktober 10. Helmholtz Metadata Collaboration Konferenz 2023 (HMC 2023), Online, 10.–12. Oktober 2023

A Tool for Automatic Metadata Extraction and Schema Mapping for SEM Images
Vitali, E. G. G.; Jejkal, T.; Kirar, A.; Joseph, R. E.; Hartmann, V.; Blumenröhr, N.; Inckmann, M.; Aversa, R.; Stotzka, R.
2023, Oktober 10. Helmholtz Metadata Collaboration Konferenz 2023 (HMC 2023), Online, 10.–12. Oktober 2023

Enhancing Usability in Linked Data Editing in Web Applications
Pfeil, A.
2023, Oktober 10. Helmholtz Metadata Collaboration Konferenz 2023 (HMC 2023), Online, 10.–12. Oktober 2023

Towards Research Object Crates 1.2, with ro-crate-java
Pfeil, A.
2023, Oktober 10. Helmholtz Metadata Collaboration Konferenz 2023 (HMC 2023), Online, 10.–12. Oktober 2023

A Short Introduction to the Data Collections Explorer
Ost, P.
2023. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000162885

MatterMiners/tardis: 0.8.0
Giffels, M.; Fischer, M.; Haas, A.; Kroboth, S.; Schnepf, M.; Kuehn, E.; Schuhmacher, P.; Caspart, R.; Cube, F. von; Sammel, D.; Rottler, B.; Wienemann, P.
2023, Oktober. doi:10.5281/zenodo.8426261

Improvement of temperature uniformity by using novel guide vanes in solar external receiver tubes
Long, Y.; Tu, Z.; Piccioni Koch, D.; Frank, M.; Zhu, R.
2023. Applied Thermal Engineering, 233, Art.-Nr.: 121182. doi:10.1016/j.applthermaleng.2023.121182

RelaxNet: A structure-preserving neural network to approximate the Boltzmann collision operator
Xiao, T.; Frank, M.
2023. Journal of Computational Physics, 490, Art.-Nr.: 112317. doi:10.1016/j.jcp.2023.112317

Boosting Distributional Copula Regression
Hans, N.; Klein, N.; Faschingbauer, F.; Schneider, M.; Mayr, A.
2023. Biometrics, 79 (3), 2298–2310. doi:10.1111/biom.13765

Certificate-based OpenSSH for Federated Identities. Masterarbeit
Brocke, L.
2023, September 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000165236

Der krönende Abschluss: Paläographische Besonderheiten im Kontext der automatischen Texterkennung
Frank, L.; Ernst, F.; Götzelmann, G.
2023. P. Helling, P. Gietz & M. Derntl (Hrsg.), FORGE 2023 - Forschungsdaten in den Geisteswissenschaften: Anything Goes?! Forschungsdaten in den Geisteswissenschaften - kritisch betrachtet. Konferenzabstracts, Ed.: M. Derntl. doi:10.5281/zenodo.8386432

EVOKS - Benutzerfreundliche Erstellung kontrollierter Vokabulare für die Geisteswissenschaften
Ernst, F.; Frank, L.; Götzelmann, G.; Eckhardt, K.; Maly, J.; Preker, Y.; Scholz, J.
2023. P. Helling, P. Gietz & M. Derntl (Hrsg.), FORGE 2023 - Forschungsdaten in den Geisteswissenschaften: Anything Goes?! Forschungsdaten in den Geisteswissenschaften - kritisch betrachtet. Konferenzabstracts, Ed.: M. Derntl. doi:10.5281/zenodo.8386468

Building a Data Transfer Federation between Research Centers
Farhadi, M.; Sushkov Evdoshenko, S.; Petzold, A.
2023, September 28. NFDI4Ing Conference (2023), Online, 27.–28. September 2023

A numerical study of a cold-mode fluidized bed reactor designed for pyrolysis of plastics
Zhang, F.; Tavakkol, S.; Dercho, S.; Bohlender, L.; Zirwes, T.; Zeller, M.; Vogt, J.; Stapf, D.
2023, September 28. 31. Deutscher Flammentag (2023), Berlin, Deutschland, 27.–28. September 2023

An assessment of fluidized bed dynamics with CPFD simulations
Zhang, F.; Tavakkol, S.; Dercho, S.; Bohlender, L.; Zirwes, T.; Zeller, M.; Vogt, J.; Stapf, D.
2023, September 28. 31. Deutscher Flammentag (2023), Berlin, Deutschland, 27.–28. September 2023

Inverse design of all-dielectric metasurfaces with accidental bound states in the continuum
Gladyshev, S.; Karamanos, T. D.; Kuhn, L.; Beutel, D.; Weiss, T.; Rockstuhl, C.; Bogdanov, A.
2023. Nanophotonics, 12 (19), 3767–3779. doi:10.1515/nanoph-2023-0373

Successful stories in NFFA-Europe Pilot and beyond
Aversa, R.
2023, September 26. NFFA-Europe Workshop: FAIR and Open Data in NFFA-Europe Pilot and Beyond (2023), Garching bei München, Deutschland, 26. September 2023. doi:10.5281/zenodo.8383121

Long Term Interoperability of Distributed Research Data Infrastructures
Politze, M.; Shakeel, Y.; Hunke, S.; Ost, P.; Aversa, R.; Heinrichs, B.; Lang, I.
2023, September 13. 1st Conference on Research Data Infrastructure (CoRDI 2023), Karlsruhe, Deutschland, 12.–14. September 2023

Landscaping European Competence Centres: Skills4EOSC case study
Berberi, L.; Lazzeri, E.; Leister, C.
2023, September 12. 1st Conference on Research Data Infrastructure (CoRDI 2023), Karlsruhe, Deutschland, 12.–14. September 2023. doi:10.5281/zenodo.8349135

Data Collections Explorer – An Easy-to-Use Tool for Sharing and Discovering Research Data
Ost, P.; Shakeel, Y.; Tögel, P.
2023, September 12. 1st Conference on Research Data Infrastructure (CoRDI 2023), Karlsruhe, Deutschland, 12.–14. September 2023

Proton reconstruction with the CMS-TOTEM Precision Proton Spectrometer
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2023. Journal of Instrumentation, 18 (09), P09009. doi:10.1088/1748-0221/18/09/P09009

Three-dimensional effects on the local and global structure of thermo-diffusive instabilities in premixed hydrogen flames
Zirwes, T.; Zhang, F.; Kaiser, T. L.; Eckart, S.; Oberleithner, K.; Stein, O. T.; Bockhorn. H.
2023, September. 31. Deutscher Flammentag (2023), Berlin, Deutschland, 27.–28. September 2023

A numerical study of a cold-mode fluidized bed reactor designed for pyrolysis of plastics
Zhang, F.; Tavakkol, S.; Dercho, S.; Bohlender, L.; Zirwes, T.; Zeller, M.; Vogt, J.; Stapf, D.
2023. 31. Deutscher Flammentag für Nachhaltige Verbrennung 2023, Berlin, 27. und 28. September 2023

An assessment of fluidized bed dynamics with CPFD simulations
Zhang, F.; Tavakkol, S.; Bohlender, L.; Dercho, S.; Zirwes, T.; Zeller, M.; Vogt, J.; Stapf, D.
2023. 31. Deutscher Flammentag

Predicting continuum breakdown with deep neural networks
Xiao, T.; Schotthöfer, S.; Frank, M.
2023. Journal of Computational Physics, 489, Art.-Nr.: 112278. doi:10.1016/j.jcp.2023.112278

indigo-dc/oidc-agent: oidc-agent 5.0.0
Zachmann, G.; Hardt, M.
2023, August 30. doi:10.5281/zenodo.8300672

From implementation to application: FAIR digital objects for training data composition
Blumenröhr, N.; Aversa, R.
2023. Research Ideas and Outcomes, 9, e108706. doi:10.3897/rio.9.e108706

Providing AI expertise as an infrastructure in academia
Piraud, M.; Camero, A.; Götz, M.; Kesselheim, S.; Steinbach, P.; Weigel, T.
2023. Patterns, 4 (8), Art.-Nr.: 100819. doi:10.1016/j.patter.2023.100819

Constraints on anomalous Higgs boson couplings to vector bosons and fermions from the production of Higgs bosons using the τ τ final state
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2023. Physical Review D, 108 (3), 032013. doi:10.1103/PhysRevD.108.032013

A survey of the European Open Science Cloud services for expanding the capacity and capabilities of multidisciplinary scientific applications
Calatrava, A.; Asorey, H.; Astalos, J.; Azevedo, A.; Benincasa, F.; Blanquer, I.; Bobak, M.; Brasileiro, F.; Codó, L.; del Cano, L.; Esteban, B.; Ferret, M.; Handl, J.; Kerzenmacher, T.; Kozlov, V.; u. a.
2023. Computer Science Review, 49, Artkl.Nr.: 100571. doi:10.1016/j.cosrev.2023.100571

Integrating batched sparse iterative solvers for the collision operator in fusion plasma simulations on GPUs
Kashi, A.; Nayak, P.; Kulkarni, D.; Scheinberg, A.; Lin, P.; Anzt, H.
2023. Journal of Parallel and Distributed Computing, 178, 69–81. doi:10.1016/j.jpdc.2023.03.012

Soiling determination for parabolic trough collectors based on operational data analysis and machine learning
Brenner, A.; Kahn, J.; Hirsch, T.; Röger, M.; Pitz-Paal, R.
2023. Solar Energy, 259, 257–276. doi:10.1016/j.solener.2023.05.008

MetaStore v1.3.0
Hartmann, V.; Jejkal, T.; Chelbi, S.
2023, Juli 7. doi:10.5281/zenodo.8123797

Approximate Bayesian Computation for Parameter Identification in Computational Mechanics
Faes, M. G. R.; Klein, N.; Pauly, M.; Valdebenito, M. A.; Misraji, M. A.
2023. 14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP14, Dublin, Ireland, July 9-13, 2023, 1–7

MatterMiners/cobald: v0.14.0
Fischer, M.; Kuehn, E.; Giffels, M.; Schnepf, M.; Kroboth, S.; Thorsten, M.; Freyermuth, O.
2023, Juli. doi:10.5281/zenodo.8199049

Search for a massive scalar resonance decaying to a light scalar and a Higgs boson in the four b quarks final state with boosted topology
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2023. Physics Letters B, 842, Art.-Nr.: 137392. doi:10.1016/j.physletb.2022.137392

Modelling the response of a turbulent jet flame to acoustic forcing in a linearized framework using an active flame approach
Kaiser, T. L.; Varillon, G.; Polifke, W.; Zhang, F.; Zirwes, T.; Bockhorn, H.; Oberleithner, K.
2023. Combustion and Flame, 253, Art.-Nr.: 112778. doi:10.1016/j.combustflame.2023.112778

Marginally calibrated response distributions for end-to-end learning in autonomous driving
Hoffmann, C.; Klein, N.
2023. The Annals of Applied Statistics, 17 (2), 1740–1763. doi:10.1214/22-AOAS1693

Computational Studies of Transmembrane Proteins. Dissertation
Kumar, D.
2023, Juni 30. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000152704

A Controlled Vocabulary for Acronyms of NFDI-MatWerk Using the Vocabulary Service EVOKS
Abdildina, G.; Ernst, F.; Aversa, R.; Ost, P.
2023, Juni 29. 1st NFDI-MatWerk Conference on Digital Transformation in Materials Science and Engineering (2023), Siegburg, Deutschland, 27.–29. Juni 2023

Linking Research Data
Kirar, A.; Hunke, S.; Aversa, R.; Stotzka, R.; Heinrichs, B.; Shakeel, Y.; Joseph, R. E.
2023, Juni 29. 1st NFDI-MatWerk Conference on Digital Transformation in Materials Science and Engineering (2023), Siegburg, Deutschland, 27.–29. Juni 2023

Enhancing Multi-Scale Simulations of Charge and Exciton Transfer with Machine Learning Methods. Dissertation
Dohmen, P. M.
2023, Juni 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000156196

Demonstration of the Infrastructure Use Case 02: Framework for curation and distribution of reference datasets
Hammerschmidt, T.; Forti, M.; Ávila, L. A. Calderón; Olbricht, J.; Skrotzki, B.; Gedsun, A.; Shakeel, Y.; Stotzka, R.
2023, Juni 27. 1st NFDI-MatWerk Conference on Digital Transformation in Materials Science and Engineering (2023), Siegburg, Deutschland, 27.–29. Juni 2023

Framework for Curation and Distribution of Reference Datasets Example: Creep Data of Ni-Base Superalloys
Ávila, L. A. Calderón; Hammerschmidt, T.; Shakeel, Y.; Gedsun, A.; Olbricht, J.; Aversa, R.; Stotzka, R.; Skrotzki, B.
2023, Juni 27. 1st NFDI-MatWerk Conference on Digital Transformation in Materials Science and Engineering (2023), Siegburg, Deutschland, 27.–29. Juni 2023

Data Collections Explorer – An Information System for the Engineering Sciences
Ost, P.; Stotzka, R.
2023, Juni 27. 1st NFDI-MatWerk Conference on Digital Transformation in Materials Science and Engineering (2023), Siegburg, Deutschland, 27.–29. Juni 2023

Applying Metadata Management: Extraction, Mapping & Visualisation
Abdildina, G.; Heinrichs, B.; Joseph, R. E.; Kirar, A.; Vitali, E. G. G.; Aversa, R.
2023

Metadata Extraction Tool and Schema Mapper for Scanning Electron Microscopy (SEM) images
Vitali, E. G. G.; Kirar, A.; Joseph, R. E.; Hartmann, V.; Blumenröhr, N.; Aversa, R.; Stotzka, R.
2023, Juni 27. 1st NFDI-MatWerk Conference on Digital Transformation in Materials Science and Engineering (2023), Siegburg, Deutschland, 27.–29. Juni 2023

Approximation and Optimization of Global Environmental Simulations with Neural Networks
Azmi, E.; Meyer, J.; Strobl, M.; Weimer, M.; Streit, A.
2023. PASC ’23: Proceedings of the Platform for Advanced Scientific Computing Conference Platform for Advanced Scientific Computing Conference (2023) Davos, Schweiz, 26.06.2023–28.06.2023, Art.-Nr.: 19, Association for Computing Machinery (ACM). doi:10.1145/3592979.3593418

mytoken - secure long-lived tokens for you - everywhere
Zachmann, G.; Hardt, M.; Gudu, D. M.
2023, Juni 21. EGI Conference (2023), Poznań, Polen, 19.–23. Juni 2023

Unraveling the effect of hydrogenation on the mechanical properties of coiled carbon nanotubes: a molecular dynamics study
Saray, M. A.; Baghani, M.; Rajabpour, A.; Sharifian, A.; Baniassadi, M.
2023. Physical Chemistry Chemical Physics, 25 (23), 15988–16000. doi:10.1039/D3CP00894K

Building a Data Transfer Federation
Farhadi, M.; Skopnik, P.
2023, Juni 14. Workshop for Efficient Data Handling, Data Exchange and Storage Performance (2023), Göttingen, Deutschland, 14. Juni 2023

DS2STAC: A Python package for harvesting and ingesting (meta)data into STAC-based catalog infrastructures
Hadizadeh, M.; Lorenz, C.; Barthlott, S.; Fösig, R.; Çayoğlu, U.; Ulrich, R.; Bach, F.
2023, Juni 9. 8th Data Science Symposium (2023), Kiel, Deutschland, 8.–9. Juni 2023. doi:10.5281/zenodo.8086566

Synergies between Numerical Methods for Kinetic Equations and Neural Networks. Dissertation
Schotthöfer, S.
2023, Juni 5. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000158838

Deep distributional time series models and the probabilistic forecasting of intraday electricity prices
Klein, N.; Smith, M. S.; Nott, D. J.
2023. Journal of Applied Econometrics, 38 (4), 493–511. doi:10.1002/jae.2959

Maschinelles Lernen im Schulunterricht am Beispiel einer problemorientierten Lerneinheit zur Wortvorhersage
Hofmann, S.; Frank, M.
2023. 56. Jahrestagung der Gesellschaft für Didaktik der Mathematik, 157–160, WTM Verlag für wissenschaftliche Texte und Medien. doi:10.17877/DE290R-23317

Training: Bringing your AI models to EOSC
Heredia, I.; Alibabaei, K.; Calatrava, A.; Kozlov, V.
2023, Juni. EGI Conference (2023), Poznań, Polen, 19.–23. Juni 2023

MLOps platforms review: case study for AI4EOSC
Berberi, L.; Kozlov, V.; Céspedes Sisniega, J.; Lopez Garcia, A.
2023, Juni. EGI Conference (2023), Poznań, Polen, 19.–23. Juni 2023. doi:10.13140/RG.2.2.13326.33609

MSLE: An ontology for materials science laboratory equipment – Large-scale devices for materials characterization
Jalali, M.; Mail, M.; Aversa, R.; Kübel, C.
2023. Materials Today Communications, 35, Art.-Nr.: 105532. doi:10.1016/j.mtcomm.2023.105532

The Three-Phase Contact Potential Difference Modulates the Water Surface Charge
Artemov, V.; Frank, L.; Doronin, R.; Stärk, P.; Schlaich, A.; Andreev, A.; Leisner, T.; Radenovic, A.; Kiselev, A.
2023. The Journal of Physical Chemistry Letters, 14 (20), 4796–4802. doi:10.1021/acs.jpclett.3c00479

Improvements of the Density-Functional Tight-Binding Parameters and Their Application in Histidine Kinase. Dissertation
Kansari, M.
2023, Mai 25. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000155207

Boosting multivariate structured additive distributional regression models
Strömer, A.; Klein, N.; Staerk, C.; Klinkhammer, H.; Mayr, A.
2023. Statistics in Medicine, 42 (11), 1779–1801. doi:10.1002/sim.9699

Modelling intra-annual tree stem growth with a distributional regression approach for Gaussian process responses
Riebl, H.; Klein, N.; Kneib, T.
2023. Journal of the Royal Statistical Society Series C: Applied Statistics, 72 (2), 414–433. doi:10.1093/jrsssc/qlad015

Dropout Regularization in Extended Generalized Linear Models based on Double Exponential Families
Schwienhorst, B. L.; Kock, L.; Klein, N.; Nott, D. J.
2023. arxiv

Uncertainty quantification and numerical methods in charged particle radiation therapy. Dissertation
Stammer, P.
2023, Mai 4. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000158316

CAG-Repeat RNA Hairpin Folding and Recruitment to Nuclear Speckles with a Pivotal Role of ATP as a Cosolute
Hautke, A.; Hautke, A.; Voronin, A.; Idiris, F.; Riel, A.; Lindner, F.; Lelièvre-Büttner, A.; Zhu, J.; Appel, B.; Fatti, E.; Weis, K.; Müller, S.; Schug, A.; Ebbinghaus, S.
2023. Journal of the American Chemical Society, 145 (17), 9571–9583. doi:10.1021/jacs.2c13653

MatterMiners/tardis: 0.7.1
Giffels, M.; Fischer, M.; Haas, A.; Kroboth, S.; Schnepf, M.; Kuehn, E.; PSchuhmacher; Caspart, R.; Cube, F. von; Sammel, D.; Rottler, B.; LGTM Migrator; Wienemann, P.
2023, Mai. doi:10.5281/zenodo.7943895

Extracting, Mapping, Editing SEM Metadata
Aversa, R.; Joseph, R.; Vitali, E.; Kirar, A.
2023, April 26. 1st Generelle KIT-Informationsveranstaltung MaTeLiS Pilot-Projekt Gerätepool (2023), Online, 26. April 2023

O3as: Ozone trend visualisations and return dates developed within within EOSC-synergy
Kerzenmacher, T.; Kozlov, V.; Esteban Sanchis, B.; Cayoglu, U.; Hardt, M.; Braesicke, P.
2023, April 24. European Geosciences Union General Assembly (EGU 2023), Wien, Österreich, 23.–28. April 2023. doi:10.5194/egusphere-egu23-15375

Metadata Extraction and Mapping Service
Joseph, R. E.; Vitali, E. G. G.; Kirar, A.; Aversa, R.
2023, April 14. National Research Data Infrastructure for Materials Science and Engineering TA-MDI Working Meeting RWTH Aachen (NFDI-MatWerk 2023), Aachen, Deutschland, 12.–14. April 2023

MetaStore v1.2.3
Hartmann, V.; Jejkal, T.; Chelbi, S.
2023, April 13. doi:10.5281/zenodo.7825567

Implicit propagation of directly addressed grids in lattice Boltzmann methods
Kummerländer, A.; Dorn, M.; Frank, M.; Krause, M. J.
2023. Concurrency and Computation: Practice and Experience, 35 (8), Art.-Nr.: e7509. doi:10.1002/cpe.7509

KCDS Virtual Open House - Project 03 Optimization and acceleration of aerosol dynamics and chemistry subprocesses in weather and climate models
Cayoglu, U.
2023. (A. Hühnerfuß, Hrsg.)

A Flux Reconstruction Stochastic Galerkin Scheme for Hyperbolic Conservation Laws
Xiao, T.; Kusch, J.; Koellermeier, J.; Frank, M.
2023. Journal of Scientific Computing, 95 (1), 18. doi:10.1007/s10915-023-02143-3

Experimental and numerical investigation of flame stabilization and pollutant formation in matrix stabilized ammonia-hydrogen combustion
Vignat, G.; Zirwes, T.; Toro, E. R.; Younes, K.; Boigné, E.; Muhunthan, P.; Simitz, L.; Trimis, D.; Ihme, M.
2023. Combustion and Flame, 250, Article no: 112642. doi:10.1016/j.combustflame.2023.112642

Process Insights into Perovskite Thin‐Film Photovoltaics from Machine Learning with In Situ Luminescence Data
Laufer, F.; Ziegler, S.; Schackmar, F.; Viteri, E. A. M.; Götz, M.; Debus, C.; Isensee, F.; Paetzold, U. W.
2023. Solar RRL, 7 (7), Art.-Nr.: 2201114. doi:10.1002/solr.202201114

KCDS Virtual Open House - Project 04 Exploring the Potential of machine learning methods for improving operational hydrological forecasting and prediction (EPOforHydro)
Ehret, U.; Krumscheid, S.
2023. (A. Hühnerfuß, Hrsg.)

KCDS Virtual Open House - Project 02 Deep Boltzmann - Structure-preserving deep neural networks to accelerate the solution of the Boltzmann equation
Frank, M.
2023. (A. Hühnerfuß, Hrsg.)

Development of a scoring function for comparing simulated and experimental tumor spheroids
Herold, J.; Behle, E.; Rosenbauer, J.; Ferruzzi, J.; Schug, A.
2023. (P. M. Altrock, Hrsg.) PLOS Computational Biology, 19 (3), Art.-Nr. e1010471. doi:10.1371/journal.pcbi.1010471

Token solutions from KIT for SSH with OIDC
Hardt, M.; Zachmann, G.; Gudu, D.
2023, März 23. International Symposium on Grids & Clouds (ISGC 2023), Taipeh, Taiwan, 19.–24. März 2023

IG FAIR Digital Object Fabric
Stotzka, R.; Chen, X.; Hellström, M.; Quick, R.
2023, März 22. 20th RDA Plenary Meeting (2023), Göteborg, Schweden, 21.–23. März 2023

FAIR DO Applications: Achievements and Challenges
Blumenröhr, N.
2023, März 22. 20th RDA Plenary Meeting (2023), Göteborg, Schweden, 21.–23. März 2023

How FAIR DOs Enable Interoperability
Stotzka, R.; Chen, X.; Hellström, M.; Quick, R.
2023, März 20. Global Research Commons: Europe And Beyond (2023), Göteborg, Schweden, 20. März 2023

Schrifttradition digital: Rituell reine Torarollen in der jüdischen Diaspora
Frank, L.; Eichhorst, D.; Ullrich, R.; Haddassah Wendl, K.; Martini, A.; Tonne, D.
2023. DHd2023: Open Humanities, Open Culture. Konferenzabstracts. Hrsg.: A. Busch, 283–286, Zenodo. doi:10.5281/zenodo.7715864

Creating Exemplary RDM Reference Datasets: Technical Process Overview
Shakeel, Y.; Abdildina, G.; Aversa, R.; Ávila, L. A. Calderón; Blumenröhr, N.; Diebels, S.; Engstler, M.; Fell, J.; Fritzen, F.; Hartmann, V.; Herrmann, H.-G.; Jejkal, T.; Joseph, R.; Kirar, A.; Laadhar, A.; u. a.
2023, März 9. All-Hands-on-Deck congress from the NFDI-MatWerk (2023), Siegburg, Deutschland, 8.–9. März 2023

Metadata Extraction Tool and Schema Mapper for Scanning Electron Microscopy (SEM) images
Vitali, E. G. G.; Joseph, R. E.; Aversa, R.
2023, März 9. 2nd National Research Data Infrastructure for Materials Science and Engineering : All-Hands-on-Deck (NFDI-MatWerk 2023), Siegburg, Deutschland, 8.–9. März 2023

Conceptual Map of TA-MDI Results
Aversa, R.; Abdildina, G.; Chelbi, S.; Ernst, F.; Jejkal, T.; Joseph, R.; Kirar, A.; Ost, P.; Pfeil, A.; Shakeel, Y.; Stotzka, R.; Vitali, E.; Grünwald, K.; Hunke, S.; Moghaddam, A.; u. a.
2023, März 9. 2nd National Research Data Infrastructure for Materials Science and Engineering : All-Hands-on-Deck (NFDI-MatWerk 2023), Siegburg, Deutschland, 8.–9. März 2023

The Scheme for a Metadata Schema - Unlocking the Power of Schemas
Joseph, R. E.; Aversa, R.
2023, März 9. 2nd Workshop "Joint Lab : Integrated Model and Data Driven Material Characterization" (MDMC 2023), Jülich, Deutschland, 8.–10. März 2023

Proposed MDI – Architecture Concept Draft
Shakeel, Y.; Hunke, S.
2023, März 8. 2nd National Research Data Infrastructure for Materials Science and Engineering : All-Hands-on-Deck (NFDI-MatWerk 2023), Siegburg, Deutschland, 8.–9. März 2023

A robust collision source method for rank adaptive dynamical low-rank approximation in radiation therapy
Kusch, J.; Stammer, P.
2023. ESAIM: Mathematical Modelling and Numerical Analysis, 57 (2), 865–891. doi:10.1051/m2an/2022090

Exploiting graph neural networks to perform finite-difference time-domain based optical simulations
Kuhn, L.; Repän, T.; Rockstuhl, C.
2023. APL Photonics, 8 (3), Article no: 036109. doi:10.1063/5.0139004

Impact of carbon dioxide and nitrogen addition on the global structure of hydrogen flames
Eckart, S.; Pio, G.; Zirwes, T.; Zhang, F.; Salzano, E.; Krause, H.; Bockhorn, H.
2023. Fuel, 335, Art.-Nr.: 126929. doi:10.1016/j.fuel.2022.126929

Constructing relaxation systems for lattice Boltzmann methods
Simonis, S.; Frank, M.; Krause, M. J.
2023. Applied Mathematics Letters, 137, Art.-Nr.: 108484. doi:10.1016/j.aml.2022.108484

Machine learning-based conditional mean filter: A generalization of the ensemble Kalman filter for nonlinear data assimilation
Hoang, T.-V.; Krumscheid, S.; Matthies, H. G.; Tempone, R.
2023. Foundations of Data Science, 5, 56–80. doi:10.3934/fods.2022016

MetaStore
Hartmann, V.; Jejkal, T.; Chelbi, S.
2023, Februar 28. doi:10.5281/zenodo.7685007

Scanning Electron Microscopy (SEM) - Metadata extraction tool and schema mapper
Joseph, R. E.; Vitali, E. G. G.; Aversa, R.
2023, Februar 27. MaRDA Annual Meeting (2023), Online, 21.–23. Februar 2023. doi:10.21955/materialsopenres.1115090.1

Adaptive Stratification (ADSS)
Krumscheid, S.; Pettersson, P.; Yuan, F.
2023, Februar 21. doi:10.5281/zenodo.7660514

base-repo v1.3.0
Jejkal, T.; Hartmann, V.
2023, Februar 21. doi:10.5281/zenodo.7660036

Helmholtz Metadata Collaboration, Helmholtz Kernel Information Profile
Curdt, C.; Günther, G.; Jejkal, T.; Koch, C.; Krebs, F.; Pfeil, A.; Pirogov, A.; Schweikert, J.; Videgain Barranco, P.; Weinelt, M.
2023. HMC Office, GEOMAR Helmholtz Centre for Ocean Research. doi:10.3289/HMC_publ_03

MatterMiners/tardis: The Escape
Giffels, M.; Fischer, M.; Haas, A.; Kroboth, S.; Schnepf, M.; Kuehn, E.; PSchuhmacher; Caspart, R.; Cube, F. von; LGTM Migrator; Wienemann, P.
2023, Februar. doi:10.5281/zenodo.7680164

Towards cellular digital twins of in vivo tumors
Behle, E.; Herold, J. M.; Schug, A. H.
2023. Biophysical Journal, 122 (3 Supplement 1), 301a–302a. doi:10.1016/j.bpj.2022.11.1700

Using machine learning to parametrize large scale tumor simulations
Herold, J. M.; Behle, E.; Schug, A. H.
2023. Biophysical Journal, 122 (3 Supplement 1), 413a. doi:10.1016/j.bpj.2022.11.2243

Extending the distributed computing infrastructure of the CMS experiment with HPC resources
Adelman-McCarthy, J.; Boccali, T.; Caspart, R.; Delgado Peris, A.; Fischer, M.; Flix Molina, J.; Giffels, M.; Hernández, J. M.; Hufnagel, D.; Kühn, E.; Madlener, T.; Mohapatra, A. K.; Ozturk, H.; Pérez-Calero Yzquierdo, A.; Spiga, D.; u. a.
2023. Journal of Physics: Conference Series, 2438 (1), Artkl.Nr.: 012039. doi:10.1088/1742-6596/2438/1/012039

Deep learning approaches to building rooftop thermal bridge detection from aerial images
Mayer, Z.; Kahn, J.; Hou, Y.; Götz, M.; Volk, R.; Schultmann, F.
2023. Automation in Construction, 146, Art.-Nr.: 104690. doi:10.1016/j.autcon.2022.104690

Modeling of radiation heat transfer in dense-bed flows of solids in indirectly heated rotary kilns
Tavakkol, S.; Zirwes, T.; Denev, J. A.; Bockhorn, H.; Stapf, D.
2023. Thermal Science and Engineering Progress, 38, Article no: 101545. doi:10.1016/j.tsep.2022.101545

Multivariate error modeling and uncertainty quantification using importance (re-)weighting for Monte Carlo simulations in particle transport
Stammer, P.; Burigo, L.; Jäkel, O.; Frank, M.; Wahl, N.
2023. Journal of Computational Physics, 473, Artkel-Nr.: 111725. doi:10.1016/j.jcp.2022.111725

Artificial Intelligence for the #EOSC
Kozlov, V.
2023, Januar 13. High-Performance Computing (HPC) and Data-Intensive Computing (DIC) User Meeting (2023), Karlsruhe, Deutschland, 13. Januar 2023

Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads
Caspart, R.; Ziegler, S.; Weyrauch, A.; Obermaier, H.; Raffeiner, S.; Schuhmacher, L. P.; Scholtyssek, J.; Trofimova, D.; Nolden, M.; Reinartz, I.; Isensee, F.; Götz, M.; Debus, C.
2023. High Performance Computing. ISC High Performance 2022 International Workshops – Hamburg, Germany, May 29 – June 2, 2022, Revised Selected Papers. Ed.: H. Anzt, 108–121, Springer International Publishing. doi:10.1007/978-3-031-23220-6_8

Overcoming the Limitations of Localization Uncertainty: Efficient and Exact Non-linear Post-processing and Calibration
Kassem Sbeyti, M.; Karg, M.; Wirth, C.; Nowzad, A.; Albayrak, S.
2023. Machine Learning and Knowledge Discovery in Databases: Research Track – European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part V. Ed.: D. Koutra, 52–68, Springer Nature Switzerland. doi:10.1007/978-3-031-43424-2_4

Boosting Distributional Soft Regression Trees
Umlauf, N.; Seiler, J.; Wetscher, M.; Klein, N.
2023. Proceedings of the 37th International Workshop on Statistical Modelling. Ed.: E. Bergherr, 311–316, Technische Universität Dortmund (TU Dortmund)

Complexity Reduction via Deselection for Boosting Distributional Copula Regression
Strömer, A.; Klein, N.; Staerk, C.; Klinkhammer, H.; Mayr, A.
2023. Proceedings of the 37th International Workshop on Statistical Modelling. Ed.: E. Bergherr, 300–304, Technische Universität Dortmund (TU Dortmund)

Informed Priors for Knowledge Integration in Trajectory Prediction
Schlauch, C.; Klein, N.; Wirth, C.; Klein, N.
2023. D. Koutra (Hrsg.), Machine Learning and Knowledge Discovery in Databases: Research Track : European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part V, Hrsg.: D. Koutra, C. Plant, R. M. Gomez, E. Baralis, F. Bonchi, 392–407, Springer Nature Switzerland. doi:10.1007/978-3-031-43424-2_24

The Consequences of not Completing the Generational Cohort in Estimating Age-at-Menopause
Martins, R.; Sousa, B. de; Kneib, T.; Hohberg, M.; Klein, N.; Duarte, E.; Rodrigues, V.
2023. Proceedings of the 37th International Workshop on Statistical Modelling : July 17-21, 2023, Dortmund, Germany, Ed.: E. Bergherr, A. Groll, A. Mayr, 502–506

A Distributional Regression Approach for Gaussian Process Responses
Kneib, T.; Riebl, H.; Klein, N.
2023. Proceedings of the 37th International Workshop on Statistical Modelling July 17-21, 2023 - Dortmund, Germany. Ed.: E. Bergherr, 279–284, Technische Universität Dortmund (TU Dortmund)

Predicting cycling traffic in cities: Is bikesharing data representative of the cycling volume
Kaiser, S. K.; Klein, N.; Kaack, L. H.
2023. 11th International Conference on Learning Representations (ICLR 2023): Tackling Climate Change with Machine Learning Workshop

deepregression : A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression
Rügamer, D.; Kolb, C.; Fritz, C.; Pfisterer, F.; Kopper, P.; Bischl, B.; Shen, R.; Bukas, C.; Barros de Andrade e Sousa, L.; Thalmeier, D.; Baumann, P. F. M.; Kook, L.; Klein, N.; Müller, C. L.
2023. Journal of Statistical Software, 105 (2). doi:10.18637/jss.v105.i02

perun: Benchmarking Energy Consumption of High-Performance Computing Applications
Gutiérrez Hermosillo Muriedas, J. P.; Flügel, K.; Debus, C.; Obermaier, H.; Streit, A.; Götz, M.
2023. Euro-Par 2023: Parallel Processing. Ed.: J. Cano, 17–31, Springer Nature Switzerland. doi:10.1007/978-3-031-39698-4_2

MLflow and its usage
Kozlov, V.; Alibabaei, K.; Esteban Sanchis, B.; Berberi, L.
2023. AI4EOSC Platform User Workshop (2023), Bratislava, Slowakei, 15.–16. November 2023. doi:10.13140/RG.2.2.32801.17761

The MIPAS global climatology of BrONO2 2002–2012 in comparison to EMAC model data
Höpfner, M.; Kirner, O.; Wetzel, G.; Sinnhuber, B.-M.; Haenel, F.; Johansson, S.; Orphal, J.; Ruhnke, R.; Stiller, G.; Clarmann, T.
2023. doi:10.35097/1484

Reporting electricity consumption is essential for sustainable AI
Debus, C.; Piraud, M.; Streit, A.; Theis, F.; Götz, M.
2023. Nature Machine Intelligence, 5 (11), 1176–1178. doi:10.1038/s42256-023-00750-1

Templates Hub for research communities
Esteban Sanchis, B.; Laures, C.; Hardt, M.; Kozlov, V.
2023. 12th IberGrid "Better Software for Better Science" (2023), Benasque, Spanien, 25.–29. September 2023

iMagine: imaging data and services for aquatic science
Kozlov, V.; Sipos, G.; Schaap, D.; López Garcia, A.
2023. 38th ISC High Performance Computing (ISC HPC 2023), Hamburg, Deutschland, 22.–25. Mai 2023

D6.1 : Analysis of user applications, collection of requirements
Berberi, L.; Heredia, I.; Kozlov, V.; Vollmer, E.; Sainz-Pardo, J.; Bartok, J.; Fojud, A.; Blaszczak, M.; Rausch, A.; Alibabaei, K.
2023. Zenodo. doi:10.5281/zenodo.7635453

D1.2 : AI4EOSC Data Management Plan
Aguilar, F.; Kozlov, V.; Heredia, I.
2023. Zenodo. doi:10.5281/zenodo.7649075

D3.1 : State of the art landscaping and initial platform requirements specification
Moltó, G.; Calatrava, A.; Nguyen, G.; Díaz, J. S.-P.; Berberi, L.; Kozlov, V.; Cruz, M. S.
2023. Zenodo. doi:10.5281/zenodo.7635430

iMagine D3.1 : Technical development roadmap for the AI image analysis use cases
Kozlov, V.
2023. Zenodo. doi:10.5281/zenodo.7760413

D3.2 : Initial High Level Architecture
García, Á. L.; Berberi, L.; Kozlov, V.; Antonacci, M.; Calatrava, A.; Langarita, S.; Moltó, G.
2023. Zenodo. doi:10.5281/zenodo.7728882

Global sensitivity analysis of a one-dimensional ocean biogeochemical model
Mamnun, N.; Völker, C.; Krumscheid, S.; Vrekoussis, M.; Nerger, L.
2023. Socio-Environmental Systems Modelling, 5, Art.-Nr.: 18613. doi:10.18174/sesmo.18613

NilsNiggemann/PMFRG.jl: MPI support
Nils Niggemann; Michele Mesiti
2023. doi:10.5281/zenodo.10404917

Sequential-Stratified-LHS Estimator
Krumscheid, S.; Pettersson, P.
2023. doi:10.5281/zenodo.10402170

Cat4KIT: A Cross-institutional Data Catalog Framework for the FAIRification of Environmental Research Data
Hadizadeh, M.; Lorenz, C.; Barthlott, S.; Fösig, R.; Çayoğlu, U.; Ulrich, R.; Bach, F.
2023. E-Science-Tage 2023. Hrsg.: V. Heuveline, 149–160, heiBOOKS. doi:10.11588/heibooks.1288.c18072

Stochastic upscaling for UP with OPM and ADSS
Pettersson, P.; Keilegavlen, E.; Sandve, T. H.; Gasda, S.; Krumscheid, S.
2023. doi:10.5281/zenodo.10362253

MetadataHub: Demonstrator UI
Heinrichs, B.; Hartmann, V.
2023. doi:10.5281/zenodo.10354788

MetadataHub: Multi Store Search UI
Heinrichs, B.; Hartmann, V.
2023. doi:10.5281/zenodo.10158732

Specification of Turntable API for Metadata Repositories
Hartmann, V.; Heinrichs, B.
2023. doi:10.5281/zenodo.10351292

MetadataHub
Hartmann, V.; Heinrichs, B.
2023. doi:10.5281/zenodo.10351597

Data Competence for Photonic Nanotechnologies
Meyer, J.; Asadova, N.; Beutel, D.; Çayoğlu, U.; Rockstuhl, C.; Tristram, F.
2023. E-Science-Tage 2023. Empower Your Research – Preserve Your Data. Eds.: Vincent Heuveline, Nina Bisheh und Philipp Kling, 301–305, heiBOOKS. doi:10.11588/heibooks.1288.c18092

Low-Cost Three-Dimensionally Printed Inverted Plug and Play Optical Instrument for Microfluidic Imaging
Markov, D.; Grigorov, E.; Kirov, B.; Denev, J. A.; Galabov, V.; Marinov, M. B.
2023. Micro, 3 (2), 537–548. doi:10.3390/micro3020036

GPU-resident sparse direct linear solvers for alternating current optimal power flow analysis
Świrydowicz, K.; Koukpaizan, N.; Ribizel, T.; Göbel, F.; Abhyankar, S.; Anzt, H.; Peleš, S.
2023. doi:10.48550/arXiv.2306.14337

Numerical simulation of thermal decomposition of polyethylene with a single-particle model
Zhang, F.
2023. 14th International Conference on Computational Heat and Mass Transfer (ICCHMT 2023), Düsseldorf, Deutschland, 4.–8. September 2023

A community‐endorsed open‐source lexicon for contrast agent–based perfusion MRI : A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI)
on behalf of The Perfusion Study Group of the ISMRM; Dickie, B. R.; Ahmed, Z.; Arvidsson, J.; Bell, L. C.; Buckley, D. L.; Debus, C.; Fedorov, A.; Floca, R.; Gutmann, I.; van der Heijden, R. A.; van Houdt, P. J.; Sourbron, S.; Thrippleton, M. J.; Quarles, C.; u. a.
2023. Magnetic Resonance in Medicine. doi:10.1002/mrm.29840

A search for new physics in central exclusive production using the missing mass technique with the CMS detector and the CMS-TOTEM precision proton spectrometer
CMS and TOTEM Collaborations; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; u. a.
2023. The European Physical Journal C, 83 (9), Art - Nr.: 827. doi:10.1140/epjc/s10052-023-11687-5

An iterative methodology for REDIM reduced chemistry generation and its validation for partially-premixed combustion
Shrotriya, P.; Schießl, R.; Yu, C.; Bykov, V.; Zirwes, T.; Maas, U.
2023. Combustion Theory and Modelling, 1–34. doi:10.1080/13647830.2023.2260350

Long Term Interoperability of Distributed Research Data Infrastructures
Politze, M.; Shakeel, Y.; Hunke, S.; Ost, P.; Aversa, R.; Heinrichs, B.; Lang, I.
2023. Proceedings of the Conference on Research Data Infrastructure, 1. doi:10.52825/cordi.v1i.348

Data Collections Explorer – An Easy-to-Use Tool for Sharing and Discovering Research Data
Ost, P.; Shakeel, Y.; Tögel, P.
2023. Proceedings of the Conference on Research Data Infrastructure. Ed.: Y. Sure-Vetter. Vol. 1, 3 S., Technische Informationsbibliothek Open Publishing (TIB Open Publishing). doi:10.52825/cordi.v1i.405

RNA contact prediction by data efficient deep learning
Taubert, O.; von der Lehr, F.; Bazarova, A.; Faber, C.; Knechtges, P.; Weiel, M.; Debus, C.; Coquelin, D.; Basermann, A.; Streit, A.; Kesselheim, S.; Götz, M.; Schug, A.
2023. Communications Biology, 6 (1), 913. doi:10.1038/s42003-023-05244-9

AI/ML-based support of satellite sensing for cloud cover classification. Masterarbeit
Wessel, E.
2023. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000161948

Sparse matrix‐vector and matrix‐multivector products for the truncated SVD on graphics processors
Aliaga, J. I.; Anzt, H.; Quintana-Ortí, E. S.; Tomás, A. E.
2023. Concurrency and Computation: Practice and Experience, 35 (28), Art.-Nr.: e7871. doi:10.1002/cpe.7871

Collaboration through reuse: Analyzing letters explored by others
Tögel, P.
2023. Digital Humanities 2023: Book of Abstracts. Ed.: A. Baillot, 471–472, Zenodo. doi:10.5281/zenodo.8108012

Search for light Higgs bosons from supersymmetric cascade decays in collisions at
CMS Collaboration; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; u. a.
2023. The European Physical Journal C, 83 (7), Art.-Nr.: 571. doi:10.1140/epjc/s10052-023-11581-0

Measurement of the differential production cross section as a function of the jet mass and extraction of the top quark mass in hadronic decays of boosted top quarks
CMS Collaboration; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; u. a.
2023. The European Physical Journal C, 83 (7), Art.-Nr.: 560. doi:10.1140/epjc/s10052-023-11587-8

Assessment of Numerical Accuracy and Parallel Performance of OpenFOAM and its Reacting Flow Extension EBIdnsFoam
Zirwes, T.; Sontheimer, M.; Zhang, F.; Abdelsamie, A.; Pérez, F. E. H.; Stein, O. T.; Im, H. G.; Kronenburg, A.; Bockhorn, H.
2023. Flow, Turbulence and Combustion, 111 (2), 567–602. doi:10.1007/s10494-023-00449-8

Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations
Taubert, O.; Weiel, M.; Coquelin, D.; Farshian, A.; Debus, C.; Schug, A.; Streit, A.; Götz, M.
2023. doi:10.48550/arXiv.2301.08713

Mixed Precision Algebraic Multigrid on GPUs
Tsai, Y.-H. M.; Beams, N.; Anzt, H.
2023. Parallel Processing and Applied Mathematics – 14th International Conference, PPAM 2022, Gdansk, Poland, September 11–14, 2022, Revised Selected Papers, Part I. Ed.: R. Wyrzykowski, 113 – 125, Springer International Publishing. doi:10.1007/978-3-031-30442-2_9

Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations
Taubert, O.; Weiel, M.; Coquelin, D.; Farshian, A.; Debus, C.; Schug, A.; Streit, A.; Götz, M.
2023. High Performance Computing – 38th International Conference, ISC High Performance 2023, Hamburg, Germany, May 21–25, 2023, Proceedings. Ed.: A. Bhatele, 106 – 124, Springer Nature Switzerland. doi:10.1007/978-3-031-32041-5_6

A Mixed Precision Randomized Preconditioner for the LSQR Solver on GPUs
Georgiou, V.; Boutsikas, C.; Drineas, P.; Anzt, H.
2023. High Performance Computing – 38th International Conference, ISC High Performance 2023, Hamburg, Germany, May 21–25, 2023, Proceedings. Ed.: A. Bhatele, 164 – 181, Springer Nature Switzerland. doi:10.1007/978-3-031-32041-5_9

Sp(2N) Lattice Gauge Theories and Extensions of the Standard Model of Particle Physics
Bennett, E.; Holligan, J.; Hong, D. K.; Hsiao, H.; Lee, J.-W.; Lin, C.-J. D.; Lucini, B.; Mesiti, M.; Piai, M.; Vadacchino, D.
2023. doi:10.48550/arXiv.2304.01070

FAIR Data Management Workflow for MRI Data
Aversa, R.; MacKinnon, N.; Blumenröhr, N.
2023. 3rd Workshop on Metadata and Research (objects) Management for Linked Open Science (DaMaLOS 2023) - Co-located with Extended Semantic Web Conference (ESWC), Online, 28.-29.05.2023, paper 5349. doi:10.4126/FRL01-006444992

Klassifizierungsprobleme : Maschinelles Lernen und KI im Mathematikunterricht
Schönbrodt, S.; Frank, M.
2023. Beiträge zum Mathematikunterricht 2022, Gesellschaft für Didaktik der Mathematik (GDM). doi:10.17877/DE290R-23426

Sp(2N) Lattice Gauge Theories and Extensions of the Standard Model of Particle Physics
Bennett, E.; Holligan, J.; Hong, D. K.; Hsiao, H.; Lee, J.-W.; Lin, C.-J. D.; Lucini, B.; Mesiti, M.; Piai, M.; Vadacchino, D.
2023. Universe, 9 (5), Art.-Nr.: 236. doi:10.3390/universe9050236

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures
Ayoul-Guilmard, Q.; Ganesh, S.; Krumscheid, S.; Nobile, F.
2023. International Journal for Uncertainty Quantification, 13 (5), 61–98. doi:10.1615/Int.J.UncertaintyQuantification.2023045259

Thermal Bridges on Building Rooftops
Mayer, Z.; Kahn, J.; Götz, M.; Hou, Y.; Beiersdörfer, T.; Blumenröhr, N.; Volk, R.; Streit, A.; Schultmann, F.
2023. Scientific Data, 10 (1), Art.-Nr.: 268. doi:10.1038/s41597-023-02140-z

Polynomial propagators for classical molecular dynamics
Kondov, I.
2023. arxiv. doi:10.48550/arXiv.2302.03516

An interdisciplinary approach to data management
Altschuh, P.; Bräse, S.; Hartmann, T.; Jaeger, D.; Jung, N.; Krauss, P.; Leister, C.; Nestler, B.; Schiefer, G.; Schreiber, C.; Selzer, M.; Starman, M.; Tosato, G.; Koeppe, A.
2023. E-Science-Tage 2023: Empower Your Research – Preserve Your Data (2023), Heidelberg, Deutschland, 1.–3. März 2023. doi:10.11588/heidok.00033126

Effect of nozzle up-scaling on coaxial, gas-assisted atomization
Zhang, F.; Wachter, S.; Zirwes, T.; Jakobs, T.; Zarzalis, N.; Trimis, D.; Kolb, T.; Stapf, D.
2023. Physics of Fluids, 35 (4), Art.-Nr.: 043302. doi:10.1063/5.0141156

Isotopic measurements in water vapor, precipitation, and seawater during EURECA
Bailey, A.; Aemisegger, F.; Villiger, L.; Los, S. A.; Reverdin, G.; Quiñones Meléndez, E.; Acquistapace, C.; Baranowski, D. B.; Böck, T.; Bony, S.; Bordsdorff, T.; Coffman, D.; de Szoeke, S. P.; Diekmann, C. J.; Dütsch, M.; u. a.
2023. Earth System Science Data, 15 (1), 465–495. doi:10.5194/essd-15-465-2023

Multiscale Modeling of Spheroid Tumors: Effect of Nutrient Availability on Tumor Evolution
Rosenbauer, J.; Berghoff, M.; Glazier, J. A.; Schug, A.
2023. The Journal of Physical Chemistry B, 127 (16), 3607–3615. doi:10.1021/acs.jpcb.2c08114

Peer-Reviewing and Submission Dynamics Around Top Software-Engineering Venues: A Juniors’ Perspective
Alchokr, R.; Krüger, J.; Shakeel, Y.; Saake, G.; Leich, T.
2023. T. M. Engels G. Hebig R. (Hrsg.), Software Engineering 2023 Ed.: G. Engels, 31–32, Gesellschaft für Informatik (GI)

Training Parameterized Quantum Circuits with Triplet Loss
Wendenius, C.; Kuehn, E.; Streit, A.
2023. Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings. Part V. Ed.: M.-R. Amini, 515–530, Springer Nature Switzerland. doi:10.1007/978-3-031-26419-1_31

base-repo v1.4.0
Jejkal, T.; Hartmann, V.
2023. doi:10.5281/zenodo.7744529

Metaphors of Religion
Gebhard, H.; Jha, V.; Tögel, P.; Dipper, S.; Elwert, F.; Tonne, D.
2023. DHd2023: Open Humanities, Open Culture. Konferenzabstracts. Hrsg.: A. Busch, 399–401, Zenodo. doi:10.5281/zenodo.7715325

Numerical simulations of air-assisted primary atomization at different air-to-liquid injection angles
Zhang, F.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Trimis, D.; Kolb, T.; Bockhorn, H.; Stapf, D.
2023. International journal of multiphase flow, 158, Art.-Nr.: 104304. doi:10.1016/j.ijmultiphaseflow.2022.104304

Near-wall dynamics of premixed methane/air flames
Zhu, J.; Pan, J.; Zhang, F.; Zirwes, T.; Ojo, A. O.; Li, F.
2023. Fuel, 331, Art.Nr. 125774. doi:10.1016/j.fuel.2022.125774

Using Ginkgo’s memory accessor for improving the accuracy of memory-bound low precision BLAS
Grützmacher, T.; Anzt, H.; Quintana-Ortí, E. S.
2023. Software - Practice and Experience, 531 (1), 81–98. doi:10.1002/spe.3041

Statistical Learning of Nonlinear Stochastic Differential Equations from Nonstationary Time Series using Variational Clustering
Boyko, V.; Krumscheid, S.; Vercauteren, N.
2022. Multiscale Modeling & Simulation, 20 (4), 1251–1283. doi:10.1137/21M1403989

cc-metric-collector
Gruber, T.; Obermaier, H.
2022, Dezember 14. doi:10.5281/ZENODO.7438287

Python support for OIDC Access Tokens – FLAAT
Hardt, M.; Esteban, B. Sanchis; Gudu, D.; Stevanovic, U.; Kozlov, V.
2022, Dezember 13. doi:https://doi.org/10.5281/zenodo.7433611

Whitepaper der ZKI AG edu-ID zur Verortung des Konzepts einer edu-ID in der aktuellen Landschaft digitaler Identitäten in Deutschland und Europa
Bacharach, G.; Gietz, P.; Gragert, G.; Gündogan, A.; Hardt, M.; Michels, T.; Oberknapp, B.; Pempe, W.; Pfeiffer, R.; Smidt, M.; Soldo, E.
2022. Zenodo. doi:10.5281/zenodo.7425176

Is age at menopause decreasing? – The consequences of not completing the generational cohort
Martins, R.; Sousa, B. de; Kneib, T.; Hohberg, M.; Klein, N.; Duarte, E.; Rodrigues, V.
2022. BMC Medical Research Methodology, 22 (1), Art.-Nr. 187. doi:10.1186/s12874-022-01658-x

Guidance on Versioning of Digital Assets
Buttigieg, P. L.; Cristiano, L.; Curdt, C.; Ishan, A. Z.; Jejkal, T.; Koch, C.; Mannix, O.; Mohr, D. P.; Pirogov, A.; Stucky, K. U.; Helmholtz Metadata Collaboration (HMC)
2022. (S. Lorenz, A. Finke, C. Langenbach, K. Maier-Hein, S. Sandfeld & R. Stotzka, Hrsg.), GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel. doi:10.3289/HMC_publ_04

Dynamical low-rank approximation for Marshak waves
Ceruti, G.; Frank, M.; Kusch, J.
2022. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000154134

A low-rank power iteration scheme for neutron transport criticality problems
Kusch, J.; Whewell, B.; Whewell, B.; McClarren, R.
2022. Journal of Computational Physics, 470, 111587. doi:10.1016/j.jcp.2022.111587

Hyperspectral (RGB + Thermal) drone images of Karlsruhe, Germany - Raw images for the Thermal Bridges on Building Rooftops (TBBR) dataset
Kahn, J.; Mayer, Z.; Hou, Y.; Beiersdörfer, T.; Götz, M.; Volk, R.
2022, November 25. doi:10.5281/zenodo.7360996

A Computational Workflow for Interdisciplinary Deep Learning Projects utilizing bwHPC Infrastructure
Schilling, M.; Neumann, O.; Scherr, T.; Cui, H.; Popova, A. A.; Levkin, P. A.; Götz, M.; Reischl, M.
2022. Proceedings of the 7th bwHPC Symposium, 69–74, Kommunikations- und Informationszentrum (kiz). doi:10.18725/OPARU-46069

dianagudu/motley_cue: v0.5.0
Gudu, D.; Hardt, M.
2022, November 24. doi:10.5281/zenodo.7353878

oidc-mytoken/lib: mytokenlib 0.6.1
Zachmann, G.
2022, November 22. doi:10.5281/zenodo.7346688

Dynamical stability indicator based on autoregressive moving-average models: Critical transitions and the Atlantic meridional overturning circulation
Rodal, M.; Krumscheid, S.; Madan, G.; Henry LaCasce, J.; Vercauteren, N.
2022. Chaos: An Interdisciplinary Journal of Nonlinear Science, 32 (11), Art.-Nr.: 113139. doi:10.1063/5.0089694

Correlated Coevolving Mutations at Protein–Protein Interfaces
Schug, A.
2022. Protein Interactions – The Molecular Basis of Interactomics. Ed.: V. Helms, 39–52, John Wiley and Sons. doi:10.1002/9783527830503.ch3

oidc-mytoken/server: mytoken-server 0.6.1
Zachmann, G.
2022, November 11. doi:10.5281/zenodo.7313513

EOSC-synergy/eosc-perf-frontend: v1.2.0
Laures, C.; Esteban Sanchis, B.; Kozlov, V.; Hardt, M.
2022, November 9. doi:10.5281/zenodo.7366363

Guidelines for Secure Operation of Attribute Authorities and issuers of statements for entities (G071)
Groep, D. L.; Collier, I.; Dack, T.; Jensen, J.; Kelsey, D.; Kremers, M.; Neilson, I.; Paetow, S.; Short, H.; Sallé, M.; Stevanovic, U.
2022. IGTF and AARC Community. doi:10.5281/zenodo.5927799

Implementing Asynchronous Jacobi Iteration on GPUs
Tsai, Y.-H. M.; Nayak, P.; Chow, E.; Anzt, H.
2022. 2022 IEEE/ACM Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH). IEEE/ACM Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH 2022) Dallas, TX, USA, 13.11.2022–18.11.2022, 1–9, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalAH56622.2022.00006

Numerical analysis of a developing turbulent flow and conjugate heat transfer for molten salt and liquid sodium in a solar receiver
Khuda, M. A.; Khalesi, J.; Tu, Z.; Long, Y.; Piccioni Koch, D.; Sarunac, N.
2022. Applied Thermal Engineering, 217, Art.-Nr.: 119156. doi:10.1016/j.applthermaleng.2022.119156

EOSC-synergy/o3webapp: o3webapp 1.0.1
Çevik, F.; Marwitz, T.; Prjanikov, N.; Rönn, S. von; Zeller, J.; Laures, C.; Kozlov, V.; Sanchis, B. E.; Cayoglu, U.; Kerzenmacher, T.
2022, November. doi:10.5281/zenodo.7372070

Dataset: ESACCI ozone data for O3as service (v1: zonal means and monthly means of total columns)
Esteban Sanchis, B.; Kozlov, V.; Kerzenmacher, T.
2022, November. doi:10.35097/832

Dataset: SBUV ozone measurements for O3as service (v1: zonal means and monthly means of total columns)
Esteban Sanchis, B.; Kozlov, V.; Kerzenmacher, T.
2022, November. doi:10.35097/831

A FAIR Digital Object Lab Software Stack
Pfeil, A.
2022, Oktober 27. 1st International Conference of FAIR Digital Objects (FDO 2022), Leiden, Niederlande, 26.–28. Oktober 2022

Methodisch-didaktische Entwicklung und Evaluation von interaktiven Lehr- und Lernmaterialien zur Mathematik im Bereich der Klimaforschung. Dissertation
Hattebuhr, M.
2022, Oktober 21. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000151547

New Work - Erfahrungen der Piloten - Pilotprojekt SCC
Kühn, E.
2022. (I. Hartmann-Dietsch & M. Landgraf, Hrsg.)

Compare computing sites using EOSC-Performance service
Esteban-Sachnis, B.; Laures, C.
2022, Oktober 13. 11th IberGrid "Better Software for Better Science" (2022), Faro, Portugal, 10.–14. Oktober 2022

FAIR Digital Object Application Case for Composing Machine Learning Training Data
Blumenröhr, N.; Jejkal, T.; Pfeil, A.; Stotzka, R.
2022. Research Ideas and Outcomes, 8, Art.-Nr.: e94113. doi:10.3897/rio.8.e94113

SSH with Federated Identities
Zachmann, G.; Gudu, D.; Hardt, M.
2022, Oktober 12. 11th IberGrid "Better Software for Better Science" (2022), Faro, Portugal, 10.–14. Oktober 2022

Ozone assessment service (O3as) in action
Kerzenmacher, T.; Kozlov, V.; Braesicke, P.; Cayoglu, U.; Esteban Sanchis, B.; Hardt, M.
2022, Oktober 11. 11th IberGrid "Better Software for Better Science" (2022), Faro, Portugal, 10.–14. Oktober 2022

NFDI4Ing Data Collections Explorer
Ost, P.
2022, Oktober 7

oidc-mytoken/client: mytoken 0.5.2
Zachmann, G.
2022, Oktober 6. doi:10.5281/zenodo.7152846

Using Schema-based Metadata for Image Labels accessed with FAIR Digital Objects
Blumenröhr, N.; Aversa, R.
2022, Oktober 5. 1st Helmholtz Metadata Collaboration Konferenz 2023 (HMC 2022), Online, 5.–6. Oktober 2022. doi:10.5281/zenodo.7243871

FAIR DO Application Case for Composing Machine Learning Training Data
Blumenröhr, N.; Jejkal, T.; Pfeil, A.; Stotzka, R.
2022, Oktober 5. 1st Helmholtz Metadata Collaboration Konferenz 2023 (HMC 2022), Online, 5.–6. Oktober 2022. doi:10.5281/zenodo.7243865

indigo-dc/oidc-agent: oidc-agent 4.4.0
Zachmann, G.
2022, Oktober 5. doi:10.5281/zenodo.7148014

Domain level ontology design: DISO and MDMC-NEP Provenance
Ihsan, A. Z.; Fathalla, S.; Aversa, R.; Jalali, M.; Panighel, M.; Osmenaj, E.; Hofmann, V.; Sandfeld, S.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022. doi:10.5281/zenodo.7432171

FAIR DO Cookbook – Recipes for FAIR Digital Objects
Pfeil, A.; Jejkal, T.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

Research Object Crates – Bundling Research (Meta-)Data
Scholz, J.; Tzotchev, N.; Pfeil, A.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

MetaStore - Managing Metadata for Digital Objects
Hartmann, V.; Jejkal, T.; Chelbi, S.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

Metadata Hub - One for All
Hartmann, V.; Heinrichs, B.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

Annotating Humanities Research Data - Episteme, Metaphors and the Torah
Ernst, F.; Frank, L.; Götzelmann, G.; Jha, V.; Tögel, P.; Tonne, D.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

NFDI MatWerk / Materials Data Infrastructure
Stotzka, R.; Aversa, R.; Bitzek, E.; Golowin, N.; Grünwald, K.; Hunke, S.; Joseph, R.; Moghaddam, A.; Ost, P.; Politze, M.; Shakeel, Y.; Soysal, M.; Vitali, E.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

FAIR Data Commons / Essential Services and Tools for Metadata Management Supporting Science
Stotzka, R.; Abdildina, G.; Aversa, R.; Blumenröhr, N.; Chelbi, S.; Duda, L.; Ernst, F.; Frank, L.; Götzelmann, G.; Hartmann, V.; Inckmann, M.; Jejkal, T.; Jha, V.; Joseph, R.; Ost, P.; u. a.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

A basic Helmholtz Kernel Information Profile for machine-actionable FAIR Digital Objects
Jejkal, T.; Pfeil, A.; Schweikert, J.; Pirogov, A.; Barranco, P. V.; Krebs, F.; Koch, C.; Günther, G.; Curdt, C.; Weinelt, M.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

FAIR-DOscope - Explore the facets of FAIR Digital Objects
Jejkal, T.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

Data Collections Explorer
Ost, P.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

NFDI-MatWerk - Reference Datasets
Shakeel, Y.; Soysal, M.; Vitali, E.; Ost, P.
2022, Oktober 5. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes
Marques, I.; Kneib, T.; Klein, N.
2022. Statistics and Computing, 32 (5), Art.-Nr. 73. doi:10.1007/s11222-022-10136-9

Variational inference and sparsity in high-dimensional deep Gaussian mixture models
Kock, L.; Klein, N.; Nott, D. J.
2022. Statistics and Computing, 32 (5), Art.-Nr. 70. doi:10.1007/s11222-022-10132-z

FAIR Digital Object Lab
Pfeil, A.; Chelbi, S.; Jejkal, T.
2022, Oktober. doi:10.5281/zenodo.13488862

Flame-vortex interaction during turbulent side-wall quenching and its implications for flamelet manifolds
Steinhausen, M.; Zirwes, T.; Ferraro, F.; Scholtissek, A.; Bockhorn, H.; Hasse, C.
2022. Proceedings of the Combustion Institute, 39 (2), 2149–2158. doi:10.1016/j.proci.2022.09.026

EOSC-synergy/eosc-perf-backend: eosc-perf backend 1.2.0
Esteban Sanchis, B.; Laures, C.; Kozlov, V.; Hardt, M.
2022, Oktober. doi:10.5281/zenodo.7376156

EOSC-synergy/o3api: o3api 0.8.5
Kozlov, V.; Esteban Sanchis, B.; Kerzenmacher, T.
2022, Oktober. doi:10.5281/zenodo.7358926

FAIR DO Lab – A FAIR Digital Object Lab for your research
Pfeil, A.; Chelbi, S.; Jejkal, T.
2022, Oktober. Helmholtz Metadata Collaboration | Conference 2022 (2022), Online, 5.–6. Oktober 2022

EOSC-Performance: compare EOSC sites for your needs
Kozlov, V.; Esteban Sanchis, B.; Laures, C.; Hardt, M.
2022, September 22. EGI Conference (2022), Prag, Tschechien, 19.–23. September 2022

Motley-cue: SSH access with OIDC tokens
Gudu, D.; Zachmann, G.; Hardt, M.
2022, September 21. EGI Conference (2021), Online, 18.–22. Oktober 2021

OIDC support for Windows using PuTTY
Zachmann, G.; Gudu, D.; Hardt, M.
2022, September 20. EGI Conference (2021), Online, 18.–22. Oktober 2021

Hyde: The First Open-Source, Python-Based, Gpu-Accelerated Hyperspectral Denoising Package
Coquelin, D.; Rasti, B.; Gotz, M.; Ghamisi, P.; Gloaguen, R.; Streit, A.
2022. 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Rome, Italy, 13-16 September 2022, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS56178.2022.9955088

Typed PID Maker
Pfeil, A.; Jejkal, T.
2022, September 9. doi:10.5281/zenodo.8014937

Learning tree structures from leaves for particle decay reconstruction
Kahn, J.; Tsaklidis, I.; Taubert, O.; Reuter, L.; Dujany, G.; Boeckh, T.; Thaller, A.; Goldenzweig, P.; Bernlochner, F.; Streit, A.; Götz, M.
2022. Machine Learning: Science and Technology, 3 (3), Art.Nr. 035012. doi:10.1088/2632-2153/ac8de0

NFFA-Europe Pilot - D16.3 - Identification of good practices for data provenance
Yakutovich, A.; Pizzi, G.; Marzari, N.; Aversa, R.; Brandino, G. P.; Panighel, M.
2022. Zenodo. doi:10.5281/zenodo.7057955

NFFA-Europe Pilot - D16.2 - Report on the first data services
Franzon, M.; Osmenaj, E.; Panighel, M.; Rodani, T.; Brandino, G. P.; Aversa, R.
2022. Zenodo. doi:10.5281/zenodo.7057941

Thermal Bridges on Building Rooftops - Hyperspectral (RGB + Thermal + Height) drone images of Karlsruhe, Germany, with thermal bridge annotations
Mayer, Z.; Kahn, J.; Hou, Y.; Beiersdörfer, T.; Blumenröhr, N.; Götz, M.; Volk, R.
2022, August 25. doi:10.5281/zenodo.7022736

A Java Library for RO-Crate
Tzotchev, N.; Pfeil, A.
2022, August 25. 56th Research Object Crate Community Calls (2022), Online, 25. August 2022

An interpretation of the FAIR principles to guide implementations in the HMC digital ecosystem
Helmholtz Metadata Collaboration (HMC); Buttigieg, P. L.; Curdt, C.; Ishan, A. Z.; Jejkal, T.; Kubin, M.; Mannix, O.; Mohr, D. P.; Pirogov, A.; Port, B.; Stucky, K.-U.
2022. (S. Lorenz, Hrsg.), GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel. doi:10.3289/HMC_publ_01

oidc-mytoken/server: mytoken-server 0.5.0
Zachmann, G.
2022, August 23. doi:10.5281/zenodo.7016387

Measurements and Modelling of Total Ozone Columns near St. Petersburg, Russia
Nerobelov, G.; Timofeyev, Y.; Virolainen, Y.; Polyakov, A.; Solomatnikova, A.; Poberovskii, A.; Kirner, O.; Al-Subari, O.; Smyshlyaev, S.; Rozanov, E.
2022. Remote Sensing, 14 (16), 3944. doi:10.3390/rs14163944

Lowest Common Ancestor Generations (LCAG) Phasespace Particle Decay Reconstruction Dataset
Kahn, J.; Taubert, O.; Tsaklidis, I.; Reuter, L.; Dujany, G.; Boeckh, T.; Thaller, A.; Goldenzweig, P.; Bernlochner, F.; Streit, A.; Götz, M.
2022, August 11. doi:10.5281/zenodo.6983258

EOSC-synergy/o3skim: o3skim 0.9.1
Esteban, B. Sanchis; Kerzenmacher, T.; Kozlov, V.
2022, August 5. doi:10.5281/zenodo.7467555

Mitigating spatial confounding by explicitly correlating Gaussian random fields
Marques, I.; Kneib, T.; Klein, N.
2022. Environmetrics, 33 (5), Art.-Nr. e2727. doi:10.1002/env.2727

ro-crate-java
Tzochev, N.; Pfeil, A.; Chelbi, S.; Jejkal, T.
2022, Juli 14. doi:10.5281/zenodo.8075683

EOSC-synergy/eosc-perf-frontend: v1.1.0
Laures, C.; Esteban, B. Sanchis; Kozlov, V.; Hardt, M.
2022, Juli 12. doi:10.5281/zenodo.7409598

EOSC-synergy/o3skim: o3skim 0.8.5
Esteban, B. Sanchis; Kerzenmacher, T.; Kozlov, V.
2022, Juli 4. doi:10.5281/zenodo.7465188

EOSC-synergy/eosc-perf-backend: eosc-perf-backend 1.1.0
Esteban Sanchis, B.; Laures, C.; Kozlov, V.; Hardt, M.
2022, Juli. doi:10.5281/zenodo.7375700

CCMI-1 ozone data for O3as service (v1: zonal means and monthly averages)
Esteban Sanchis, B.; Kerzenmacher, T.; Kozlov, V.
2022, Juli. doi:10.35097/675

Correlation of heat loss with quenching distance during transient flame-wall Interaction
Zhang, F.
2022, Juli. 39th International Symposium on Combustion (2022), Vancouver, Kanada, 24.–29. Juli 2022

Effects of low-temperature chemical reactions on ignition kernel development and flame propagation in a DME-air mixing layer
Wang, Y.; Han, W.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2022. Proceedings of the Combustion Institute, 39 (2), 1515–1524. doi:10.1016/j.proci.2022.07.024

Multiscale Molecular Dynamics Simulations of Histidine Kinase Activity. Dissertation
Idiris, F.
2022, Juni 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000147727

indigo-dc/oidc-agent: oidc-agent 4.3.0
Zachmann, G.; Dehtyarow, D.
2022, Juni 23. doi:10.5281/zenodo.6697387

A common PID Kernel Information Profile for the German Helmholtz Association of Research Centres
Jejkal, T.; Pfeil, A.; Schweikert, J.; Pirogov, A.; Barranco, P. V.; Krebs, F.; Koch, C.; Günther, G.; Curdt, C.; Weinelt, M.
2022, Juni 21. 19th International Data Week : A Festival of Data / Plenary meeting (RDA 2022), Seoul, Südkorea, 20.–23. Juni 2022

FAIR Digital Object Concept for Composing Machine Learning Training Data
Blumenröhr, N.; Jejkal, T.; Stotzka, R.
2022, Juni 20. 19th International Data Week : A Festival of Data / Plenary meeting (RDA 2022), Seoul, Südkorea, 20.–23. Juni 2022

Structures of Small Platinum Cluster Anions Pt: Experiment and Theory
Bumüller, D.; Yohannes, A. G.; Kohaut, S.; Kondov, I.; Kappes, M. M.; Fink, K.; Schooss, D.
2022. The Journal of Physical Chemistry A, 126 (22), 3502–3510. doi:10.1021/acs.jpca.2c02142

Enhanced sampling methods applied to chemical reactions in proteins. Dissertation
Maag, D. M.
2022, Juni 7. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000146741

FAIR Digital Object for Accessing Label Information of ML Training Data Stored in a Metadata Schema
Blumenröhr, N.; Jejkal, T.; Pfeil, A.; Stotzka, R.
2022, Juni 2. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2022), Dresden, Deutschland, 2.–3. Juni 2022

quantum-triplet-loss
Wendenius, C.; Kuehn, E.
2022, Juni 1. doi:10.5281/zenodo.6786443

A Process Warehouse for Process Variants Analysis
Berberi, L.
2022. KITopen. doi:10.5445/IR/1000146946

Application and Optimization of Contact-Guided Replica Exchange Molecular Dynamics. Dissertation
Voronin, A.
2022, Mai 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000146554

cirKITers/masKIT: Version 0.1.0
Kuehn, E.; Wendenius, C.; Metz, N.
2022, Mai 13. doi:10.5281/zenodo.6702370

Thermal Bridges on Building Rooftops - Hyperspectral (RGB + Thermal + Height) drone images of Karlsruhe, Germany, with thermal bridge annotations
Mayer, Z.; Kahn, J.; Hou, Y.; Beiersdörfer, T.; Götz, M.; Volk, R.
2022, Mai 11. doi:10.5281/zenodo.6517768

Training Quantum Kernels for Clustering Algorithms. Masterarbeit
Metz, N.
2022, Mai 2. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000148603

Altmetrics and Citation Counts: An Empirical Analysis of the Computer Science Domain
Shakeel, Y.; Alchokr, R.; Krüger, J.; Saake, G.; Leich, T.
2022

Ginkgo—A math library designed for platform portability
Cojean, T.; Tsai, Y.-H. M.; Anzt, H.
2022. Parallel Computing, 111, Art.-Nr.: 102902. doi:10.1016/j.parco.2022.102902

Incorporating Altmetrics to Support Selection and Assessment of Publications during Literature Analyses
Shakeel, Y.; Alchokr, R.; Krüger, J.; Saake, G.; Leich, T.
2022

V-FOR-WaTer - a virtual research environment for environmental research
Strobl, M.; Azmi, E.; Hassler, S. K.; Mälicke, M.; Meyer, J.; Streit, A.; Zehe, E.
2022. E-Science-Tage 2021: Share Your Research Data. Hrsg.: V. Heuveline, 394–398, Heidelberger E-Books (heiBOOKS). doi:10.11588/heibooks.979.c13755

Modeling of radiation heat transfer in the dense-bed flow of solid pyrolysis in indirectly heated rotary kilns
Tavakkol, S.
2022. Proceedings of the 13th European Conference on Industrial Furnaces and Boilsers (INFUB)

Selection of representative structures from large biomolecular ensembles
Voronin, A.; Schug, A.
2022. The Journal of Chemical Physics, 156 (14), Art.-Nr.: 144102. doi:10.1063/5.0082444

Mathematische Modellierungswochen – auch online
Schönbrodt, S.; Hofmann, S.
2022. Mitteilungen der Deutschen Mathematiker-Vereinigung, 30 (1), 46–50. doi:10.1515/dmvm-2022-0016

ssciwr/hammingdist: 0.15.0
Keegan, L.; Kempf, D.; Obermaier, H.; Schreiner, H.
2022, April 11. doi:10.5281/zenodo.6448163

Guidelines for expressing group membership and role information (AARC-G069)
Ardizzone, V.; Bučík, D. F.; Hardt, M.; Helmert, S.; Jensen, J.; Kanakarakis, I.; Kanellopoulos, C.; Liampotis, N.; Linden, M.; Sallé, M.
2022. Zenodo. doi:10.5281/zenodo.6533400

A specification for providing information about an end service to a Discovery Service (AARC-G063)
Liampotis, N.; Jensen, J.; Sallé, M.; Kanellopoulos, C.; Kanakarakis, I.; Linden, M.; Ardizzone, V.
2022. (M. Hardt, Hrsg.). doi:10.5281/zenodo.6938616

Numerical Study on Flame Stabilization and NO Formation in a Novel Burner System for Sulfur Combustion
Zhang, F.; Kurjata, M.; Sebbar, N.; Zirwes, T.; Fedoryk, M.; Harth, S.; Wang, R.; Habisreuther, P.; Trimis, D.; Bockhorn, H.
2022. Energy and Fuels, 36 (7), 4094–4106. doi:10.1021/acs.energyfuels.1c04007

Correcting for sample selection bias in Bayesian distributional regression models
Wiemann, P. F. V.; Klein, N.; Kneib, T.
2022. Computational Statistics & Data Analysis, 168, 107382. doi:10.1016/j.csda.2021.107382

Evaluation of Application Possibilities for Packaging Technologies in Canonical Workflows
Jejkal, T.; Chelbi, S.; Pfeil, A.; Wittenburg, P.
2022. Data Intelligence, 4 (2), 372–385. doi:10.1162/dint_a_00137

Flame structure analysis and composition space modeling of thermodiffusively unstable premixed hydrogen flames. Part II. Elevated pressure
Wen, X.; Zirwes, T.; Scholtissek, A.; Böttler, H.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. Combustion and Flame, 238, Art.Nr. 111808. doi:10.1016/j.combustflame.2021.111808

Flame structure analysis and composition space modeling of thermodiffusively unstable premixed hydrogen flames. Part I. Atmospheric pressure
Wen, X.; Zirwes, T.; Scholtissek, A.; Böttler, H.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. Combustion and Flame, 238, Art.Nr. 111815. doi:10.1016/j.combustflame.2021.111815

NFFA-Europe Pilot - D9.1 - Deployment of the VA service prototypes
Aversa, R.; Brandino, G. P.; Chelbi, S.; Hartmann, V.; Jejkal, T.
2022. Zenodo. doi:10.5281/zenodo.7057084

SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors
Li, C.; Budde, M.; Tremper, P.; Schäfer, K.; Riesterer, J.; Redelstein, J.; Petersen, E.; Khedr, M.; Liu, X.; Köpke, M.; Hussain, S.; Ernst, F.; Kowalski, M.; Pesch, M.; Werhahn, J.; u. a.
2022. ProScience, 8. doi:10.14644/dust2021.001

Die Aktualität des Unzeitgemäßen
Krewet, M.; Ernst, F.; Götzelmann, G.; Hegel, P.; Schenk, T.; Söring, S.; Tonne, D.
2022. DHd2022: Kulturen des digitalen Gedächtnisses. Konferenzabstracts, Hrsg: M. Geierhos, 75–78. doi:10.5281/zenodo.6328015

Optimierungsprobleme in der mathematischen Modellierung : Grundlegende Aspekte und Chancen aus Sicht der Mathematikdidaktik – herausgestellt an aktuellen Problemen aus der Forschung zu künstlicher Intelligenz und erneuerbaren Energien. Dissertation
Schönbrodt, S.
2022, März 10. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000143530

Multivariate conditional transformation models
Klein, N.; Hothorn, T.; Barbanti, L.; Kneib, T.
2022. Scandinavian Journal of Statistics, 49 (1), 116–142. doi:10.1111/sjos.12501

EOSC-synergy/o3api: o3api 0.8.0
Kozlov, V.; Esteban Sanchis, B.; Kerzenmacher, T.
2022, März. doi:10.5281/zenodo.7358519

Dynamic Provision of Heterogeneous Computing Resources for Computation- and Data-intensive Particle Physics Analyses. Dissertation
Schnepf, M. J.
2022, Februar 28. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000143165

A quality-based approach for research software and services
Orviz, P.; Bernardo, S.; David, M.; Naranjo, D.; Moltó, G.; Caballer, M.; Campos, I.; Gomes, J.; Kozlov, V.; Esteban Sanchis, B.; Hardt, M.; Braesicke, P.; Kerzenmacher, T.; Blanquer, I.
2022, Februar 23. Software Engineering : Fachtagung des GI-Fachbereichs Softwaretechnik (2022), Online, 21.–25. Februar 2022

RNA structure prediction with direct coupling analysis
Faber, C.; Bayou Zerihun, M.; Schug, A. H.
2022. Biophysical Journal, 121 (3), 204a. doi:10.1016/j.bpj.2021.11.1695

Machine learning based optimization to simulate tumor development
Herold, J. M.; Behle, E.; Schug, A. H.
2022. Biophysical Journal, 121 (3), 123a. doi:10.1016/j.bpj.2021.11.2100

Cellular ATP levels are paramount for governing stability and LLPS of CAG repeat-containing RNAs inside cell
Hautke, A.; Voronin, A.; Idiris, F.; Schug, A. H.; Ebbinghaus, S.
2022. Biophysical Journal, 121 (3), 311a. doi:10.1016/j.bpj.2021.11.1202

Large-scale simulation of tumor spheroid invasion dynamics
Behle, E.; Herold, J.; Rosenbauer, J.; Schug, A. H.
2022. Biophysical Journal, 121 (3), 165a. doi:10.1016/j.bpj.2021.11.1907

Using biomolecular simulations to interpret experimental data
Schug, A. H.
2022. Biophysical Journal, 121 (3), 321a. doi:10.1016/j.bpj.2021.11.1151

Resolvent-based modelling of coherent structures in a turbulent jet flame using a passive flame approach
Casel, M.; Oberleithner, K.; Zhang, F.; Zirwes, T.; Bockhorn, H.; Trimis, D.; Kaiser, T. L.
2022. Combustion and Flame, 236, Art.-Nr.: 111695. doi:10.1016/j.combustflame.2021.111695

Search for flavor-changing neutral current interactions of the top quark and the Higgs boson decaying to a bottom quark-antiquark pair at = 13 TeV
The CMS collaboration; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; u. a.
2022. Journal of High Energy Physics, 2022 (2), 169. doi:10.1007/JHEP02(2022)169

Accelerating neural network training with distributed asynchronous and selective optimization (DASO)
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2022. Journal of Big Data, 9 (1), 14. doi:10.1186/s40537-021-00556-1

oidc-mytoken/server: mytoken-server 0.4.0
Zachmann, G.
2022, Januar 31. doi:10.5281/zenodo.5930462

FAIR Digital Object Demonstrators 2021
Wittenburg, P.; Anders, I.; Blanchi, C.; Buurman, M.; Goble, C.; Grieb, J.; Hardisty, A.; Islam, S.; Jejkal, T.; Kálmán, T.; Kirkpatrick, C.; Lannom, L.; Lauer, T.; Manepalli, G.; Peters-von Gehlen, K.; u. a.
2022. Zenodo. doi:10.5281/zenodo.5872645

Review of guidance papers on regression modeling in statistical series of medical journals
Wallisch, C.; Bach, P.; Hafermann, L.; Klein, N.; Sauerbrei, W.; Steyerberg, E. W.; Heinze, G.; Rauch, G.
2022. (T. Mathes, Hrsg.) PLOS ONE, 17 (1), Art.-Nr.: e0262918. doi:10.1371/journal.pone.0262918

Using Background Knowledge from Preceding Studies for Building a Random Forest Prediction Model: A Plasmode Simulation Study
Hafermann, L.; Klein, N.; Rauch, G.; Kammer, M.; Heinze, G.
2022. Entropy, 24 (6), 847. doi:10.3390/e24060847

Structure Preserving Neural Networks: A Case Study in the Entropy Closure of the Boltzmann Equation
Schotthöfer, S.; Xiao, T.; Frank, M.; Hauck, C.
2022. 39th International Conference on Machine Learning, ICML 2022 Baltimore17 July 2022through 23 July 2022. Ed.: K. Chaudhuri, 19406–19433

Neue Materialien für einen realitätsbezogenen Mathematikunterricht 9 – ISTRON-Schriftenreihe
Frank, M.; Roeckerath, C. (Hrsg.)
2022. Springer-Verlag. doi:10.1007/978-3-662-63647-3

iMagine D4.1 : Best practices and guideline for developers and providers of AI-based image analytics services
Heredia, I.; Kozlov, V.
2022. Zenodo. doi:10.5281/zenodo.7372358

Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations
Schotthöfer, S.; Zangrando, E.; Kusch, J.; Ceruti, G.; Tudisco, F.
2022. doi:10.48550/arXiv.2205.13571

Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations
Schotthöfer, S.; Zangrando, E.; Kusch, J.; Ceruti, G.; Tudisco, F.
2022. 36th Conference on Neural Information Processing Systems, NeurIPS 2022, Neural information processing systems foundation

MuRiT: Efficient Computation of Pathwise Persistence Barcodes in Multi-Filtered Flag Complexes via Vietoris-Rips Transformations
Neumann, M.; Bleher, M.; Hahn, L.; Braun, S.; Obermaier, H.; Soysal, M.; Caspart, R.; Ott, A.
2022. arxiv. doi:10.48550/arXiv.2207.03394

Compressing audio signals with interactive and cloud-based learning material - a workshop for high-school students
Wohak, K.; Frank, M.
2022. Teaching Mathematics and its Applications: An International Journal of the IMA, 41 (3), 240–255. doi:10.1093/teamat/hrab009

Preconditioners for Batched Iterative Linear Solvers on GPUs
Aggarwal, I.; Nayak, P.; Kashi, A.; Anzt, H.
2022. Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation – 22nd Smoky Mountains Computational Sciences and Engineering Conference, SMC 2022, Virtual Event, August 23–25, 2022, Revised Selected Papers. Ed.: K. Doug, 38–53, Springer Nature Switzerland. doi:10.1007/978-3-031-23606-8_3

MatterMiners/cobald: v0.13.0
Fischer, M.; Kuehn, E.; Giffels, M.; Schnepf, M.; Kroboth, S.; Thorsten, M.; Freyermuth, O.
2022. doi:10.5281/zenodo.7032186

Practical field-scale simulation approaches for quantification of fault-related leakage under uncertainty
Gasda, S.; Keilegavlen, E.; Sandve, T. H.; Berge, R.; Pettersson, P.; Krumscheid, S.
2022. Proceedings of the 16th Greenhouse Gas Control Technologies Conference. 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16) 23-27 Oct 2022, 1–12. doi:10.2139/ssrn.4277020

Prediction of Optimal Solvers for Sparse Linear Systems Using Deep Learning
Funk, Y.; Götz, M.; Anzt, H.
2022. Proceedings of the 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP). Ed.: X. Li, 14–24, Society for Industrial and Applied Mathematics (SIAM). doi:10.1137/1.9781611977141.2

Teaching data science in school: Digital learning material on predictive text systems
Hofmann, S.; Frank, M.
2022. Twelfth Congress of the European Society for Research in Mathematics Education (CERME12)

Erneuerbare Energien – Modellierung und Optimierung eines Solarkraftwerks
Schönbrodt, S.
2022. Neue Materialien für einen realitätsbezogenen Mathematikunterricht. Hrsg.: M. Frank, 15–69, Springer Spektrum. doi:10.1007/978-3-662-63647-3_3

Aufbau und Einsatzmöglichkeiten des Lehr- und Lernmaterials
Gerhard, M.; Hattebuhr, M.; Schönbrodt, S.; Wohak, K.
2022. Neue Materialien für einen realitätsbezogenen Mathematikunterricht. Hrsg.: M. Frank, 7–14, Springer Spektrum. doi:10.1007/978-3-662-63647-3_2

Einführung
Frank, M.; Roeckerath, C.; Schönbrodt, S.
2022. Neue Materialien für einen realitätsbezogenen Mathematikunterricht. Hrsg.: M. Frank, 1–6, Springer Spektrum. doi:10.1007/978-3-662-63647-3_1

Data Science and Machine Learning in mathematics education: Highschool students working on the Netflix Prize
Schönbrodt, S.; Frank, M.
2022. Twelfth Congress of the European Society for Research in Mathematics Education (CERME12), Feb 2022, Bozen-Bolzano, Italy

Combined effects of heat loss and curvature on turbulent flame-wall interaction in a premixed dimethyl ether/air flame
Kaddar, D.; Steinhausen, M.; Zirwes, T.; Bockhorn, H.; Hasse, C.; Ferraro, F.
2022. Proceedings of the Combustion Institute, 39 (2), 2199–2208. doi:10.1016/j.proci.2022.08.060

Memory effects of local flame dynamics in turbulent premixed flames
Zirwes, T.; Zhang, F.; Bockhorn, H.
2022. Proceedings of the Combustion Institute, 39 (2), 2349–2358. doi:10.1016/j.proci.2022.07.187

Are Altmetrics Useful for Assessing Scientific Impact? A Survey
Shakeel, Y.; Alchokr, R.; Krüger, J.; Leich, T.; Saake, G.
2022. MEDES 2022 : 14th International Conference on Management of Digital EcoSystems, Venice, Italy, 20-21 October 2022, 144–147, ACM Digital Library

Correlation of heat loss with quenching distance during transient flame-Wall interaction
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Suntz, R.; Stapf, D.
2022. Proceedings of the Combustion Institute, 39 (2), 2037–2045. doi:10.1016/j.proci.2022.10.010

Non-destructive Material Characterization of Waste Packages with QUANTOM - 22208
Herbell, H.; Coquard, L.; Hummel, J.; Nordhardt, G.; Veltkamp, T.; Havenith, A.; Krycki, K.; Fu, B.; Helmes, C.; Doemeland, M.; Heidner, M.; Simons, F.; Köble, T.; Schumann, O.; Jesser, A.
2022

EOSC SYNERGY HANDBOOK: A Handbook targeted at Computer Centre Management, Administrators, and Users of the Infrastructure
Hardt, M.; Tran, V.
2022. doi:10.5445/IR/1000152985

A survey of the European Open Science Cloud services for expanding the capacity and capabilities of multidisciplinary scientific applications
Calatrava, A.; Asorey, H.; Astalos, J.; Azevedo, A.; Benincasa, F.; Blanquer, I.; Bobak, M.; Brasileiro, F.; Codó, L.; Cano, L. del; Esteban, B.; Ferret, M.; Handl, J.; Kerzenmacher, T.; Kozlov, V.; u. a.
2022. arxiv. doi:10.48550/ARXIV.2211.07738

A container-based workflow for distributed training of deep learning algorithms in HPC clusters
González-Abad, J.; López García, Á.; Kozlov, V. Y.
2022. doi:10.5445/IR/1000152892

A container-based workflow for distributed training of deep learning algorithms in HPC clusters
González-Abad, J.; López García, Á.; Kozlov, V. Y.
2022. Cluster Computing, 26 (5), 2815–2834. doi:10.1007/s10586-022-03798-7

Constructing relaxation systems for lattice Boltzmann methods
Simonis, S.; Frank, M.; Krause, M. J.
2022. doi:10.48550/arXiv.2208.14976

Providing performance portable numerics for Intel GPUs
Tsai, Y.-H. M.; Cojean, T.; Anzt, H.
2022. Concurrency and Computation: Practice and Experience, 35 (20), Art.-Nr.: e7400. doi:10.1002/cpe.7400

The impact of tumor metabolic activity assessed by F-FET amino acid PET imaging in particle radiotherapy of high-grade glioma patients
Waltenberger, M.; Furkel, J.; Röhrich, M.; Salome, P.; Debus, C.; Tawk, B.; Gahlawat, A. W.; Kudak, A.; Dostal, M.; Wirkner, U.; Schwager, C.; Herold-Mende, C.; Combs, S. E.; König, L.; Debus, J.; u. a.
2022. Frontiers in Oncology, 12, Art.Nr. 901390. doi:10.3389/fonc.2022.901390

A Novel Semi-supervised Clustering Algorithm: CoExDBSCAN
Ertl, B.; Schneider, M.; Meyer, J.; Streit, A.
2022. Knowledge Discovery, Knowledge Engineering and Knowledge Management – 12th International Joint Conference, IC3K 2020, Virtual Event, November 2-4, 2020, Revised Selected Papers. Ed.: A. Fred, 1–21, Springer International Publishing. doi:10.1007/978-3-031-14602-2_1

A Closer Look into Collaborative Publishing at Software-Engineering Conferences
Alchokr, R.; Krüger, J.; Shakeel, Y.; Saake, G.
2022. Linking Theory and Practice of Digital Libraries – 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, Padua, Italy, September 20–23, 2022, Proceedings. Ed.: G. Silvello, 395–402, Springer International Publishing. doi:10.1007/978-3-031-16802-4_38

Developing the EOSC-Pillar RDM Training and Support Catalogue
Garcia, P. O.; Berberi, L.; Candela, L.; Van Nieuwerburgh, I.; Lazzeri, E.; Czuray, M.
2022. Linking Theory and Practice of Digital Libraries – 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, Padua, Italy, September 20–23, 2022, Proceedings. Ed.: G. Silvello, 274–281, Springer International Publishing. doi:10.1007/978-3-031-16802-4_22

Weighted Altmetric Scores to Facilitate Literature Analyses
Shakeel, Y.; Bharti, A.; Leich, T.; Saake, G.
2022. Linking Theory :Practice of Digital Libraries – 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, Padua, Italy, September 20–23, 2022, Proceedings. Ed.: G. Silvello, 459–465, Springer. doi:10.1007/978-3-031-16802-4_46

Realizing FAIR Digital Objects for the German Helmholtz Association of Research Centres
Jejkal, T.; Pfeil, A.; Schweikert, J.; Pirogov, A.; Barranco, P.; Krebs, F.; Koch, C.; Guenther, G.; Curdt, C.; Weinelt, M.
2022. Research Ideas and Outcomes, 8, Art.Nr. e94758. doi:10.3897/rio.8.e94758

Pt nanoparticles under oxidizing conditions – implications of particle size, adsorption sites and oxygen coverage on stability
Yohannes, A. G.; Fink, K.; Kondov, I.
2022. Nanoscale Advances, 4 (21), 4554–4569. doi:10.1039/D2NA00490A

Plateau proposal distributions for adaptive component-wise multiple-try metropolis
Lau, F. D.-H.; Krumscheid, S.
2022. METRON, 80, Art.Nr. 106003. doi:10.1007/s40300-022-00235-y

Adaptive stratified sampling for non-smooth problems
Pettersson, P.; Krumscheid, S.
2022. International Journal for Uncertainty Quantification, 12 (6), 71–99. doi:10.1615/Int.J.UncertaintyQuantification.2022041034

A Process Warehouse for Process Variants Analysis
Berberi, L.
2022. Big Data Analytics and Knowledge Discovery – 24th International Conference, DaWaK 2022, Vienna, Austria, August 22–24, 2022, Proceedings. Ed.: R. Wrembel, 87–93, Springer International Publishing. doi:10.1007/978-3-031-12670-3_8

Compressed basis GMRES on high-performance graphics processing units
Aliaga, J. I.; Anzt, H.; Grützmacher, T.; Quintana-Ortí, E. S.; Tomás, A. E.
2022. The International Journal of High Performance Computing Applications, 37 (2), 82–100. doi:10.1177/10943420221115140

Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products
Schneider, M.; Ertl, B.; Tu, Q.; Diekmann, C. J.; Khosrawi, F.; Röhling, A. N.; Hase, F.; Dubravica, D.; García, O. E.; Sepúlveda, E.; Borsdorff, T.; Landgraf, J.; Lorente, A.; Butz, A.; Chen, H.; u. a.
2022. Atmospheric Measurement Techniques, 15 (14), 4339–4371. doi:10.5194/amt-15-4339-2022

Towards a Similarity Algorithm for Controlled Vocabularies Within the Digital Humanities
Ernst, F.
2022. The Semantic Web: ESWC 2022 Satellite Events ; Hersonissos, Crete, Greece, May 29 – June 2, 2022, Proceedings. Ed.: P. Groth, 179–188, Springer International Publishing. doi:10.1007/978-3-031-11609-4_33

Quantifying CH emissions in hard coal mines from TROPOMI and IASI observations using the wind-assigned anomaly method
Tu, Q.; Schneider, M.; Hase, F.; Khosrawi, F.; Ertl, B.; Necki, J.; Dubravica, D.; Diekmann, C. J.; Blumenstock, T.; Fang, D.
2022. Atmospheric Chemistry and Physics, 22 (15), 9747–9765. doi:10.5194/acp-22-9747-2022

Dynamics of Premixed Hydrogen/Air Flames in Unsteady Flow
Zhang, F.; Zirwes, T.; Wang, Y.; Chen, Z.; Bockhorn, H.; Trimis, D.; Stapf, D.
2022. Physics of Fluids, 34 (8), Art.-Nr.: 085121. doi:10.1063/5.0098883

Research data available
Berberi, L.
2022

Porting Sparse Linear Algebra to Intel GPUs
Tsai, Y. M.; Cojean, T.; Anzt, H.
2022. Euro-Par 2021: Parallel Processing Workshops – Euro-Par 2021 International Workshops, Lisbon, Portugal, August 30-31, 2021, Revised Selected Papers. Ed.: R. Chaves, 57–68, Springer International Publishing. doi:10.1007/978-3-031-06156-1_5

Towards a Network of Sixteenth Century Book Illustrations
Götzelmann, G.
2022. T. Andrews, F. Diehr, T. Efer, A. Kuczera & J. van Zundert (Hrsg.), Graph Technologies in the Humanities : Proceedings 2020. Ed.: T. Andrews, 38–59, CEUR-WS.org

Automating and Scaling Task-Level Parallelism of Tightly Coupled Models via Code Generation
Roozmeh, M.; Kondov, I.
2022. Computational Science – ICCS 2022. Pt. 4. Ed.: D. Groen, 69–82, Springer Nature Switzerland. doi:10.1007/978-3-031-08760-8_6

Investigation of spaceborne trace gas products over St Petersburg and Yekaterinburg, Russia, by using COllaborative Column Carbon Observing Network (COCCON) observations
Alberti, C.; Tu, Q.; Hase, F.; Makarova, M. V.; Gribanov, K.; Foka, S. C.; Zakharov, V.; Blumenstock, T.; Buchwitz, M.; Diekmann, C.; Ertl, B.; Frey, M. M.; Imhasin, H. K.; Ionov, D. V.; Khosrawi, F.; u. a.
2022. Atmospheric Measurement Techniques, 15 (7), 2199–2229. doi:10.5194/amt-15-2199-2022

From a Dynamic Image Annotation Process within the Humanities to a Canonical Workflow
Pfeil, A.; Jejkal, T.; Tonne, D.; Götzelmann, G.
2022. Data Intelligence, 4 (2), 386–397. doi:10.1162/dint_a_00138

Challenge of modelling GLORIA observations of upper troposphere-lowermost stratosphere trace gas and cloud distributions at high latitudes: A case study with state-of-The-Art models
Haenel, F.; Woiwode, W.; Buchmüller, J.; Friedl-Vallon, F.; Höpfner, M.; Johansson, S.; Khosrawi, F.; Kirner, O.; Kleinert, A.; Oelhaf, H.; Orphal, J.; Ruhnke, R.; Sinnhuber, B.-M.; Ungermann, J.; Weimer, M.; u. a.
2022. Atmospheric Chemistry and Physics, 22 (4), 2843–2870. doi:10.5194/acp-22-2843-2022

Design and description of the MUSICA IASI full retrieval product
Schneider, M.; Ertl, B.; Diekmann, C. J.; Khosrawi, F.; Weber, A.; Hase, F.; Höpfner, M.; García, O. E.; Sepúlveda, E.; Kinnison, D.
2022. Earth System Science Data, 14 (2), 709–742. doi:10.5194/essd-14-709-2022

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing
Anzt, H.; Cojean, T.; Flegar, G.; Göbel, F.; Grützmacher, T.; Nayak, P.; Ribizel, T.; Tsai, Y. M.; Quintana-Ortí, E. S.
2022. ACM Transactions on Mathematical Software, 48 (1), Art.-Nr.: 2. doi:10.1145/3480935

Digital Tools to Enable Collaborative Mathematical Modeling Online
Schönbrodt, S.; Wohak, K.; Frank, M.
2022. Modelling in Science Education and Learning, 15 (1), 151–174. doi:10.4995/msel.2022.16269

Partial Cross-Section Calculations for PGNAA Based on a Deterministic Neutron Transport Solver
Jesser, A.; Krycki, K.; Frank, M.
2022. Nuclear technology, 208 (7), 1114–1123. doi:10.1080/00295450.2021.2016018

Surprisingly Low Reactivity of Layered Manganese Oxide toward Water Oxidation in Fe/Ni-Free Electrolyte under Alkaline Conditions
Salmanion, M.; Kondov, I.; Vandichel, M.; Aleshkevych, P.; Najafpour, M. M.
2022. Inorganic chemistry, 61 (4), 2292–2306. doi:10.1021/acs.inorgchem.1c03665

The impact of sulfur hexafluoride (SF₆) sinks on age of air climatologies and trends
Loeffel, S.; Eichinger, R.; Garny, H.; Reddmann, T.; Fritsch, F.; Versick, S.; Stiller, G.; Haenel, F.
2022. Atmospheric chemistry and physics, 22 (2), 1175–1193. doi:10.5194/acp-22-1175-2022

Turbulent flame-wall interaction of premixed flames using Quadrature-based Moment Methods (QbMM) and tabulated chemistry: An a priori analysis
Steinhausen, M.; Zirwes, T.; Ferraro, F.; Popp, S.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. International Journal of Heat and Fluid Flow, 93, Art.-Nr.: 108913. doi:10.1016/j.ijheatfluidflow.2021.108913

Uncertainty quantification of offshore wind farms using Monte Carlo and sparse grid
Richter, P.; Wolters, J.; Frank, M.
2022. Energy Sources, Part B: Economics, Planning and Policy, 17 (1), Art.Nr. 2000520. doi:10.1080/15567249.2021.2000520

Workflow Engineering in Materials Design within the BATTERY 2030+ Project
Schaarschmidt, J.; Yuan, J.; Strunk, T.; Kondov, I.; Huber, S. P.; Pizzi, G.; Kahle, L.; Bölle, F. T.; Castelli, I. E.; Vegge, T.; Hanke, F.; Hickel, T.; Neugebauer, J.; Rêgo, C. R. C.; Wenzel, W.
2022. Advanced Energy Materials, 12 (17), Art.-Nr.: 2102638. doi:10.1002/aenm.202102638

An evaluation of tropical waves and wave forcing of the QBO in the QBOi models
Holt, L. A.; Lott, F.; Garcia, R. R.; Kiladis, G. N.; Cheng, Y.-M.; Anstey, J. A.; Braesicke, P.; Bushell, A. C.; Butchart, N.; Cagnazzo, C.; Chen, C.-C.; Chun, H.-Y.; Kawatani, Y.; Kerzenmacher, T.; Kim, Y.-H.; u. a.
2022. Quarterly journal of the Royal Meteorological Society, 148 (744), 1541–1567. doi:10.1002/qj.3827

Multidimensional Clustering for Spatio-Temporal Data and its Application in Climate Research. Dissertation
Ertl, B.
2021, Dezember 23. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000141504

D7.3: Report on the validation statistics, operational infrastructure services and recommendations for future integration work
Berberi, L.; Wezel, J. van; Breton, V.
2021. Zenodo. doi:10.5281/zenodo.5838072

Feed-Forward-Only Training of Neural Networks. Masterarbeit
Flügel, K.; Streit, A.
2021, Dezember 1. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000153057/v2

CoCoNet—boosting RNA contact prediction by convolutional neural networks
Zerihun, M. B.; Pucci, F.; Schug, A.
2021. Nucleic acids research, 49 (22), 12661–12672. doi:10.1093/nar/gkab1144

HEPiX Benchmarking Solution for WLCG Computing Resources
Giordano, D.; Alef, M.; Atzori, L.; Barbet, J.-M.; Datskova, O.; Girone, M.; Hollowell, C.; Javurkova, M.; Maganza, R.; Medeiros, M. F.; Michelotto, M.; Rinaldi, L.; Sciabà, A.; Sobie, R. J.; Southwick, D.; u. a.
2021. Computing and software for big science, 5 (1), 28. doi:10.1007/s41781-021-00074-y

Accelerated Computation of a High Dimensional Kolmogorov-Smirnov Distance
Haide, I.; Hainje, C.; Hagen, A.; Kahn, J.; Jackson, S.; Strube, J.
2021, Dezember 1. 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021), Daejeon, Südkorea, 29. November–3. Dezember 2021

OPTIMADE, an API for exchanging materials data
Andersen, C. W.; Armiento, R.; Blokhin, E.; Conduit, G. J.; Dwaraknath, S.; Evans, M. L.; Fekete, Á.; Gopakumar, A.; Gražulis, S.; Merkys, A.; Mohamed, F.; Oses, C.; Pizzi, G.; Rignanese, G.-M.; Scheidgen, M.; u. a.
2021. Scientific data, 8 (1), Art.-Nr.: 217. doi:10.1038/s41597-021-00974-z

bamlss : A Lego Toolbox for Flexible Bayesian Regression (and Beyond)
Umlauf, N.; Klein, N.; Simon, T.; Zeileis, A.
2021. Journal of Statistical Software, 100 (4). doi:10.18637/jss.v100.i04

D16.1 - Design of the service platform
Aversa, R.; Jejkal, T.; Panighel, M.; Modolo, I.; Osmenaj, E.; Brandino, G. P.
2021. Zenodo. doi:10.5281/zenodo.6984650

Quantum Computing Assisted Speech Processing. Masterarbeit
Strobl, M.
2021, November 12. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000141620

A Computational Workflow for Interdisciplinary Deep Learning Projects utilizing bwHPC Infrastructure
Schilling, M. P.; Neumann, O.; Scherr, T.; Cui, H.; Popova, A. A.; Levkin, P. A.; Götz, M.; Reischl, M.
2021, November 8. 7th bwHPC Symposium (2021), Online, 8. November 2021

Metadata Schemas for FAIR* Data in Materials Science: Scanning Electron Microscopy (SEM) Use Case : A detailed and practical schema developed in cooperation with materials scientists
Joseph, R.; Chauhan, A.; Eschke, C.; Ihsan A.; Jalali, M.; Jäntsch, U.; Jung, N.; Kumar, C. N. S.; Kübel, C.; Lucas, C.; Mail, M.; Mazilkin, A.; Neidiger, C.; Panighel, M.; Sandfeld, S.; u. a.
2021, November 4. Research Data Alliance Virtual Plenary 18 (2021), Online, 27. Oktober–11. November 2021

Memory Effects in Premixed Flames: Unraveling Transient Flame Dynamics with the Flame Particle Tracking Method. Dissertation
Zirwes, T. T.
2021, Oktober 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000139504

Federated access for SSH with OpenID Connect
Gudu, D.; Hardt, M.; Kaliszan, D.; Wolniewicz, P.
2021, Oktober 20. EGI Conference (2021), Online, 18.–22. Oktober 2021

EOSC-Performance: find most suitable EOSC site for your task
Esteban Sanchis, B.; Hardt, M.; Kozlov, V.; Laures, C.
2021, Oktober 19. EGI Conference (2021), Online, 18.–22. Oktober 2021

A Lagrangian perspective on stable water isotopes during the West African Monsoon
Diekmann, C. J.; Schneider, M.; Knippertz, P.; Vries, A. J.; Pfahl, S.; Aemisegger, F.; Dahinden, F.; Ertl, B.; Khosrawi, F.; Wernli, H.; Braesicke, P.
2021. Journal of geophysical research / D, 126 (19), e2021JD034895. doi:10.1029/2021JD034895

Collection of Job Scheduling Prediction Methods
Soysal, M.; Streit, A.
2021. Job Scheduling Strategies for Parallel Processing: 24th International Workshop, JSSPP 2021, Virtual Event, May 21, 2021, Revised Selected Papers. Ed.: D. Klusáček, 35–42, Springer-Verlag. doi:10.1007/978-3-030-88224-2_2

Heat - A Distributed and Accelerated Tensor Framework for Data Analytics and Machine Learning
Comito, C.; Götz, M.; Debus, C.; Coquelin, D.; Tarnawa, M.; Krajsek, K.; Knechtges, P.; Siggel, M.; Hagemeier, B.; Basermann, A.; Streit, A.
2021, Oktober 5. 1st Artificial Intelligence Symposium on Theory, Application & Research (AI STAR 2021), Online, 5.–6. Oktober 2021

O3as: An Ozone Trend Analysis Service within EOSC-Synergy
Kerzenmacher, T.; Kozlov, V.; Esteban Sanchis, B.; Cayoglu, U.; Hardt, M.; Braesicke, P.
2021, Oktober 3. Quadrennial Ozone Symposium (QoS 2021), Online, 3.–9. Oktober 2021

Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance
Yu, X.; Nott, D. J.; Tran, M.-N.; Klein, N.
2021. Journal of Computational and Graphical Statistics, 30 (4), 977–990. doi:10.1080/10618600.2021.1880921

Interactive Labeling for Human Pose Estimation in Surveillance Videos
Cormier, M.; Ropke, F.; Golda, T.; Beyerer, J.
2021. 2021 IEEE/CVF International Conference on Computer Vision Workshops : ICCVW 2021 : 11-17 October 2021, virtual event : proceedings. Ed.: Tamara Berg, 1649–1658, IEEEXplore. doi:10.1109/ICCVW54120.2021.00190

Analysis of Process Variants with a Process Warehouse Approach. Dissertation
Berberi, L.
2021, September 30

Simulations of Air-assisted Primary Atomization at Different Air-to-Liquid Injection Angles for Entrained Flow Gasification
Zhang, F.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Trimis, D.; Kolb, T.; Bockhorn, H.
2021. 30. Deutscher Flammentag, Deutsche Sektion des Combustion Institutes und DVV/VDI-Gesellschaft Energie und Umwelt. Ed.: F. Dinkelacker, 1116–1125

Performance prediction of scientific applications on heterogeneous HPC architectures. Masterarbeit
Höck, M.
2021, September 22. Karlsruher Institut für Technologie (KIT)

indigo-dc/oidc-agent: oidc-agent 4.2.0
Zachmann, G.
2021, September 20. doi:10.5281/zenodo.5517029

Bayesian variable selection for non‐Gaussian responses: a marginally calibrated copula approach
Klein, N.; Smith, M. S.
2021. Biometrics, 77 (3), 809–823. doi:10.1111/biom.13355

Didaktisch-methodische Entwicklung und Evaluation von computergestützten Lehr- und Lernmaterialien zur Mathematik inverser Probleme. Dissertation
Wohak, K.
2021, August 24. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000136535

The MIPAS global climatology of BrONO2 2002–2012 in comparison to EMAC model data
Höpfner, M.; Kirner, O.; Wetzel, G.; Sinnhuber, B.-M.; Haenel, F.; Johansson, S.; Orphal, J.; Ruhnke, R.; Stiller, G.; Clarmann, T. von
2021, August 16. doi:10.5445/IR/1000136324

Deriving Protein Structures Efficiently by Integrating Experimental Data into Biomolecular Simulations. Dissertation
Weiel-Potyagaylo, M.
2021, August 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000136249

oidc-mytoken/server: mytoken-server 0.3.0
Zachmann, G.
2021, August 3. doi:10.5281/zenodo.5155079

oidc-mytoken/client: mytoken 0.3.0
Zachmann, G.
2021, August 3. doi:10.5281/zenodo.5154955

A structure-preserving surrogate model for the closure of the moment system of the Boltzmann equation using convex deep neural networks
Schotthöfer, S.; Xiao, T.; Frank, M.; Hauck, C.
2021. doi:10.48550/arXiv.2106.09445

A structure-preserving surrogate model for the closure of the moment system of the Boltzmann equation using convex deep neural networks
Schotthöfer, S.; Xiao, T.; Frank, M.; Hauck, C.
2021. AIAA Aviation 2021 Forum: August 2-6, 2021 ; Virtual Event, American Institute of Aeronautics and Astronautics. doi:10.2514/6.2021-2895

EOSC-synergy/o3api: o3api 0.7.0
Kozlov, V.; Esteban Sanchis, B.; Kerzenmacher, T.
2021, August. doi:10.5281/zenodo.7358312

Correction to: Quasi-DNS Dataset of a Piloted Flame with Inhomogeneous Inlet Conditions
Zirwes, T.; Zhang, F.; Habisreuther, P.; Hansinger, M.; Bockhorn, H.; Pfitzner, M.; Trimis, D.
2021. Flow, turbulence and combustion, 107 (2), 517. doi:10.1007/s10494-021-00244-3

Heat Release Rate Markers for Highly Stretched Premixed CH/Air and CH/H/Air Flames
Chen, X.; Wang, Y.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2021. Energy & fuels, 35 (16), 13349–13359. doi:10.1021/acs.energyfuels.1c02187

Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions
Weiel, M.; Götz, M.; Klein, A.; Coquelin, D.; Floca, R.; Schug, A.
2021. Nature machine intelligence, 3 (8), 727–734. doi:10.1038/s42256-021-00366-3

Transparent Integration of Opportunistic Resources into the WLCG Compute Infrastructure
Böhler, M.; Caspart, R.; Fischer, M.; Freyermuth, O.; Giffels, M.; Kroboth, S.; Kuehn, E.; Schnepf, M.; Cube, F. von; Wienemann, P.
2021. The European physical journal / Web of Conferences, 251, Art.-Nr.: 02039. doi:10.1051/epjconf/202125102039

Hochleistungsrechner Karlsruhe (HoreKa) - Kamerafahrt durch Serverraum
Raffeiner, S.
2021. doi:10.5445/IR/1000136029

Hochleistungsrechner Karlsruhe (HoreKa)
Raffeiner, S.
2021. doi:10.5445/IR/1000136028

Interoperabilität von Metadaten innerhalb der NFDI: Konsortienübergreifender Metadaten-Workshop am 2./3. Juli 2020
Iglezakis, D.; Fuhrmans, M.; Arndt, S.; Demandt, É.; Hachinger, S.; Hausen, D.; Lanza, G.; Lipp, J.; Stotzka, R.; Terzijska, D.
2021. Bausteine Forschungsdatenmanagement, (2), 124–135. doi:10.17192/bfdm.2021.2.8313

„Geballte Rechenpower mit energieeffizienter Wasserkühlung“ - Der neue Supercomputer HoreKA des KIT wird in Betrieb genommen - Campus-Report am 27.07.2021
Fuchs, S.; Buchmüller, J.
2021. doi:10.5445/IR/1000135854

Consortium Proposal NFDI-MatWerk
Eberl, C.; Niebel, M.; Bitzek, E.; Dahmen, T.; Fritzen, F.; Gumbsch, P.; Hickel, T.; Klein, S.; Mücklich, F.; Müller, M. S.; Neugebauer, J.; Pauly, C.; Politze, M.; Sack, H.; Sandfeld, S.; u. a.
2021. Zenodo. doi:10.5281/zenodo.5082837

Bayesian Inference for Regression Copulas
Smith, M. S.; Klein, N.
2021. Journal of Business & Economic Statistics, 39 (3), 712–728. doi:10.1080/07350015.2020.1721295

EOSC-synergy/o3api: o3api 0.6.0
Kozlov, V.; Esteban Sanchis, B.; Kerzenmacher, T.
2021, Juli. doi:10.5281/zenodo.7357937

Complexity Analysis of stochastic gradient methods for PDE-constrained optimal Control Problems with uncertain parameters
Martin, M.; Krumscheid, S.; Nobile, F.
2021. ESAIM: Mathematical Modelling and Numerical Analysis, 55 (4), 1599–1633. doi:10.1051/m2an/2021025

Evolutionary Optimization of Neural Architectures in Remote Sensing Classification Problems
Coquelin, D.; Sedona, R.; Riedel, M.; Götz, M.
2021. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 12-16 July 2021, 1587–1590, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS47720.2021.9554309

Ozone assessment as an EOSC-Synergy thematic service
Braesicke, P.; Cayoglu, U.; Esteban Sanchis, B.; Hardt, M.; Kerzenmacher, T.; Kozlov, V.
2021, Juni 30. ISC High Performance (2021), Online, 24. Juni–2. Juli 2021

Mountain-wave-induced polar stratospheric clouds and their representation in the global chemistry model ICON-ART
Weimer, M.; Buchmüller, J.; Hoffmann, L.; Kirner, O.; Luo, B.; Ruhnke, R.; Steiner, M.; Tritscher, I.; Braesicke, P.
2021. Atmospheric chemistry and physics, 21 (12), 9515–9543. doi:10.5194/acp-21-9515-2021

Cells In Sillico – Parallel Tissue Development Simulation
Berghoff, M.
2021, Juni 16. Society for Mathematical Biology - Annual Meeting (SMB 2021), Online, 13.–17. Juni 2021

Progression of the CUDA TRSV implementation on an NVIDIA V100
Grützmacher, T.
2021. doi:10.5445/IR/1000133930

Guidelines for expressing community user identifiers (AARC-G026)
Hardt, M.; Jensen, J.; Kanellopoulos, C.; Sallé, M.; Kanakarakis, I.; Linden, M.
2021. (N. Liampotis, Hrsg.). doi:10.5281/zenodo.5504407

Semi-Supervised Time Point Clustering for Multivariate Time Series
Ertl, B.; Meyer, J.; Schneider, M.; Streit, A.
2021. Proceedings of the 34th Canadian Conference on Artificial Intelligence. Ed.: L. Antonie, Article: 2021L05, Canadian Artificial Intelligence Association. doi:10.21428/594757db.9fa1eff5

Bayesian Effect Selection in Structured Additive Distributional Regression Models
Klein, N.; Carlan, M.; Kneib, T.; Lang, S.; Wagner, H.
2021. Bayesian Analysis, 16 (2), 545–573. doi:10.1214/20-BA1214

Accelerated Computation of a High Dimensional Kolmogorov-Smirnov Distance
Hagen, A.; Jackson, S.; Kahn, J.; Strube, J.; Haide, I.; Pazdernik, K.; Hainje, C.
2021

Thermal Bridges on Building Rooftops - Hyperspectral (RGB + Thermal + Height) drone images of Karlsruhe, Germany, with thermal bridge annotations
Mayer, Z.; Hou, Y.; Kahn, J.; Beiersdörfer, T.; Volk, R.
2021, Mai 18. doi:10.5281/zenodo.4767772

High-Throughput screening of the CoRE MOF database to predict cross-linking of Metal-Organic Frameworks. Dissertation
Ahmad, M.
2021, Mai 12. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000132463

A stochastic kinetic scheme for multi-scale plasma transport with uncertainty quantification
Xiao, T.; Frank, M.
2021. Journal of computational physics, 432, Art.-Nr. 110139. doi:10.1016/j.jcp.2021.110139

Evaluating asynchronous Schwarz solvers on GPUs
Nayak, P.; Cojean, T.; Anzt, H.
2021. The international journal of high performance computing applications, 35 (3), 226–236. doi:10.1177/1094342020946814

An online service for analysing ozone trends within EOSC-synergy
Kerzenmacher, T.; Kozlov, V.; Esteban Sanchis, B.; Cayoglu, U.; Hardt, M.; Braesicke, P.
2021, April 27. European Geosciences Union General Assembly (EGU 2021), Online, 19.–30. April 2021. doi:10.5194/egusphere-egu21-8418

Metadata Editor
Chelbi, S.; Jejkal, T.
2021, April 20. 17th RDA Plenary Meeting (2021), Online, 20.–23. April 2021

FAIR Digital Object Ecosystem Testbed
Pfeil, A.; Jejkal, T.; Chelbi, S.; Stotzka, R.
2021, April 20. 17th RDA Plenary Meeting (2021), Online, 20.–23. April 2021

RDA Collection Registry Adoption
Jejkal, T.; Chelbi, S.; Pfeil, A.
2021, April 20. 17th RDA Plenary Meeting (2021), Online, 20.–23. April 2021

Thermal Analysis of a Solar External Receiver Tube with a Novel Component of Guide Vanes
Tu, Z.; Piccioni Koch, D.; Sarunac, N.; Frank, M.; Mao, J.
2021. Energies, 14 (8), Article no: 2253. doi:10.3390/en14082253

Marginally Calibrated Deep Distributional Regression
Klein, N.; Nott, D. J.; Smith, M. S.
2021. Journal of Computational and Graphical Statistics, 30 (2), 467–483. doi:10.1080/10618600.2020.1807996

The Trimeric Major Capsid Protein of Mavirus is stabilized by its Interlocked N-termini Enabling Core Flexibility for Capsid Assembly
Christiansen, A.; Weiel, M.; Winkler, A.; Schug, A.; Reinstein, J.
2021. Journal of Molecular Biology, 433 (7), Art.-Nr.: 166859. doi:10.1016/j.jmb.2021.166859

Adaptive Precision Block-Jacobi for High Performance Preconditioning in the Ginkgo Linear Algebra Software
Flegar, G.; Anzt, H.; Cojean, T.; Quintana-Ortí, E. S.
2021. ACM transactions on mathematical software, 47 (2), 1–28. doi:10.1145/3441850

An Eulerian-Lagrangian method for wet biomass carbonization in rotary kiln reactors
Tavakkol, S.; Zirwes, T.; Denev, J. A.; Jamshidi, F.; Weber, N.; Bockhorn, H.; Trimis, D.
2021. Renewable & sustainable energy reviews, 139, Art.-Nr.: 110582. doi:10.1016/j.rser.2020.110582

Exploring Scheduling for On-demand File Systems and Data Management within HPC Environments. Dissertation
Soysal, M.
2021, März 17. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000130537/v2

Potential of Mid-tropospheric Water Vapor Isotopes to Improve Large-Scale Circulation and Weather Predictability
Toride, K.; Yoshimura, K.; Tada, M.; Diekmann, C.; Ertl, B.; Khosrawi, F.; Schneider, M.
2021. Geophysical Research Letters, 48 (5), Art.Nr.e2020GL091698. doi:10.1029/2020GL091698

EOSC-synergy/o3skim: o3skim 0.4.0
Esteban, B. Sanchis; Kerzenmacher, T.; Kozlov, V.
2021, März 11. doi:10.5281/zenodo.7465151

EOSC-hub Configuration Management Plan
Bierenbaum, I.; Pina, J.; Weber, P.
2021. Zenodo. doi:10.5281/zenodo.4040865

A specification for IdP hinting (AARC-G061)
Kanellopoulos, C.; Liampotis, N.; Kanakarakis, I.; Linden, M.; Sallé, M.; Jensen, J.
2021. (Hardt, Marcus (ed.),, Hrsg.), Zenodo. doi:10.5281/zenodo.4596667

Kooperationsstudiengänge
Hoyer, P.; Bonenberger, T.; Bachteler, K.; Lateier, M.; Schulz, H.; Sexauer, A.; Spanke, E.; Tümmers, B.; Vogt, A.
2021. bwUni.digital. doi:10.18419/opus-11503

HyDe - Hyperspectral Denoising Algorithm Toolbox in Python
Coquelin, D.; Götz, M.
2021, Februar 23

Explanation video "Recognizing ransomware as a special type of fraudulent messages"
Burgdorf, M. (Hrsg.)
2021

Explanatory video "Recognize President Scam or CEO Fraud as a special type of fraudulent messages"
Burgdorf, M. (Hrsg.)
2021

Explanatory video "What do I pay attention to when using cloud services?"
Burgdorf, M. (Hrsg.)
2021

Explanatory video "How do I use social networks?"
Burgdorf, M. (Hrsg.)
2021

Explanatory video "What is social engineering and how do I recognize it?"
Burgdorf, M. (Hrsg.)
2021

Explanatory video "How to create a complex password"
Burgdorf, M. (Hrsg.)
2021

Explanatory video "How do I protect my information on the road or on a business trip?"
Burgdorf, M. (Hrsg.)
2021

Explanatory video "How do I protect my data around the workplace?"
Burgdorf, M. (Hrsg.)
2021

Explanatory video "Why does the topic of information security concern me?"
Burgdorf, M. (Hrsg.)
2021

Theory, models, and numerical methods for classical and non-classical transport. Dissertation
Camminady, T.
2021, Februar 1. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000128846

Cardiorespiratory, Metabolic and Perceived Responses to Electrical Stimulation of Upper‐Body Muscles While Performing Arm Cycling
Zinner, C.; Matzka, M.; Krumscheid, S.; Holmberg, H.-C.; Sperlich, B.
2021. Journal of Human Kinetics, 77 (1), 117–123. doi:10.2478/hukin-2021-0016

EOSC-synergy/o3skim: o3skim 0.2.0
Esteban Sanchis, B.; Kerzenmacher, T.; Kozlov, V.
2021, Januar 26. doi:10.5281/zenodo.7465119

EOSC Authentication and Authorization Infrastructure (AAI) : Report from the EOSC Executive Board Working Group (WG) Architecture AAI Task Force (TF)
Wierenga, K.; Johansson, L.; Kanellopoulos, C.; Groep, D.; Vaghetti, D.; Liampotis, N.; Sanden, M. van de; Reetz, J.; Alam, S.; Linden, M.; Jensen, J.; Dijk, N. van; Ceccanti, A.; Apweiler, S.; Abt, B.; u. a.
2021. European Commission (EU). doi:10.2777/8702

O3as: an online ozone trend analysis service within EOSC-synergy
Kerzenmacher, T.; Kozlov, V.; Esteban Sanchis, B.; Cayoglu, U.; Hardt, M.; Braesicke, P.
2021, Januar 22. 5th Data Science Symposium (2021), Online, 22. Januar 2021

Umfrage zur Speicherung und Langzeitarchivierung von Forschungsdaten am KIT
Zentrum für Angewandte Kulturwissenschaft und Studium Generale (ZAK) (Hrsg.)
2021, Januar 19. doi:10.35097/387

Inferring and constructing origin-affiliation information across infrastructures (AARC G057)
Groep, D.; Stevanovic, U.; Kelsey, D.; Short, H.; Neilson, I.
2021. Zenodo. doi:10.5281/zenodo.4433649

In search of lost edges: a case study on reconstructing financial networks
Lebacher, M.; Klein, N.; Kauermann, G.; Cook, S.
2021. The Journal of Network Theory in Finance, 29–61. doi:10.21314/JNTF.2019.058

The GridKa tape storage: latest improvements and current production setup
Musheghyan, H.; Ambroj Pérez, S.; Petzold, A.; Ressmann, D.; Sundermann, J. E.
2021. EPJ Web of Conferences, 251, Art.-Nr.: 02014. doi:10.1051/epjconf/202125102014

Batched Sparse Iterative Solvers for Computational Chemistry Simulations on GPUs
Aggarwal, I.; Kashi, A.; Nayak, P.; Balos, C. J.; Woodward, C. S.; Anzt, H.
2021. Proceedings of ScalA 2021: 12th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems: Held in conjunction with SC21: The International Conference for High Performance Computing, Networking, Storage and Analysis ; St. Louis, Missouri, USA, November 14-19, 2021, 35–43, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalA54577.2021.00010

Numerical Solution Strategies in Permeation Processes
Weth, A. von der; Koch, D. P.; Arbeiter, F.; Glage, T.; Klimenko, D.; Schlindwein, G.; Pasler, V.; Prothmann, N.; Zinn, K.
2021. Defect and diffusion forum, 413, 29–46. doi:10.4028/www.scientific.net/DDF.413.29

Implementation and Validation of a Computationally Efficient DNS Solver for Reacting Flows in OpenFOAM
Zirwes, T.; Zhang, F.; Habisreuther, P.; Denev, J.; Bockhorn, H.; Trimis, D.
2021. 14th WCCM-ECCOMAS Congress 2020: Collection of papers presented at the 14th edition of the WCCM-ECCOMAS, virtual congress, January, 11-15, 2021. Ed.: F. Chinesta, Scipedia S.L. doi:10.23967/wccm-eccomas.2020.175

DNS of Near Wall Dynamics of Premixed CH/Air Flames
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Suntz, R.
2021. 14th WCCM-ECCOMAS Congress 2020: Collection of papers presented at the 14th edition of the WCCM-ECCOMAS, virtual congress, January, 11-15, 2021. Ed.: F. Chinesta, Scipedia S.L. doi:10.23967/wccm-eccomas.2020.123

Hybrid eulerian-lagrangian approach for dense spray simulations
Heidarifatasmi, H.; Zirwes, T.; Zhang, F.; Habisreuther, P.; Trimis, D.
2021. Graph Drawing and Network Visualization: 29th International Symposium, GD 2021, Tübingen, Germany, September 14–17, 2021, Revised Selected Papers. Ed.: H. C. Purchase, 1–12, Scipedia S.L. doi:10.23967/wccm-eccomas.2020.172

On the analytical inversion of solver matrices used in numerical approximations for the diffusion equation
Glage, T.; Weth, A. von der; Arbeiter, F.; Koch, D. P.
2021. Defect and Diffusion Forum, 413, 3–18. doi:10.4028/www.scientific.net/DDF.413.3

Metadata schema to support FAIR data in scanning electron microscopy
Joseph, R.; Chauhan, A.; Eschke, C.; Ihsan, A. Z.; Jalali, M.; Jäntsch, U.; Jung, N.; Shyam Kumar, C. N.; Kübel, C.; Lucas, C.; Mail, M.; Mazilkin, A.; Neidiger, C.; Panighel, M.; Sandfeld, S.; u. a.
2021. Supplementary Proceedings of the XXIII International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2021): Moscow, Russia, October 26-29, 2021. Ed.: A. Pozanenko, 265–277, CEUR-WS.org

Enhancing OpenFOAM’s Performance on HPC Systems
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2021. High Performance Computing in Science and Engineering ’19 – Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2019. Ed.: W. Nagel, 225–239, Springer International Publishing. doi:10.1007/978-3-030-66792-4_16

Ad-Hoc File Systems At Extreme Scales
Soysal, M.; Streit, A.
2021. High Performance Computing in Science and Engineering ’19 – Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2019. Ed.: W. Nagel, 537–549, Springer International Publishing. doi:10.1007/978-3-030-66792-4_36

MoMaF Science Data Center für Molekulare Materialforschung
Altschuh, P.; Bach, F.; Bräse, S.; Hartmann, T.; Jung, N.; Krauß, P.; Nestler, B.; Schiefer, G.; Schreiber, C.; Selzer, M.; Terzijska, D.
2021. E-Science-Tage 2019: Data to Knowledge (2021), Heidelberg, Deutschland, 4.–5. März 2021

The Michelson Interferometer for Passive Atmospheric Sounding global climatology of BrONO2 2002–2012: a test for stratospheric bromine chemistry
Höpfner, M.; Kirner, O.; Wetzel, G.; Sinnhuber, B.-M.; Haenel, F.; Johansson, S.; Orphal, J.; Ruhnke, R.; Stiller, G.; Clarmann, T. von
2021. Atmospheric chemistry and physics, 21 (24), 18433–18464. doi:10.5194/acp-21-18433-2021

Chemotion Repository, a Curated Repository for Reaction Information and Analytical Data
Tremouilhac, P.; Huang, P.-C.; Lin, C.-L.; Huang, Y.-C.; Nguyen, A.; Jung, N.; Bach, F.; Bräse, S.
2021. Chemistry methods, 1 (1), 8–11. doi:10.1002/cmtd.202000034

NFDI4Chem – Infrastruktur für den digitalen Wandel in der Chemischen Forschung
Jung, N.; Neumann, S.; Koepler, O.; Bach, F.; Popp, C.; Herres-Pawlis, S.; Liermann, J.; Razum, M.; Steinbeck, C.
2021. Bunsen-Magazin, 23 (2), 100–103. doi:10.26125/r978-6f93

MoMaF Science Data Center für Molekulare Materialforschung
Altschuh, P.; Bach, F.; Bräse, S.; Hartmann, T.; Jung, N.; Krauß, P.; Nestler, B.; Schiefer, G.; Schreiber, C.; Selzer, M.; Terzijska, D.
2021. E-Science-Tage 2021: Share Your Research Data, Heidelberg, 04.03. - 05.03.2021. doi:10.11588/heidok.00029699

NFDI4Chem – Fachkonsortium für die Chemie - Bausteine Forschungsdatenmanagement Empfehlungen und Erfahrungsberichte für die Praxis von Forschungsdatenmanagerinnen und -managern
Ortmeyer, J.; Schön, F.; Herres-Pawlis, S.; Jung, N.; Bach, F.; Liermann, J.; Neumann, S.; Popp, C.; Razum, M.; Koepler, O.; Steinbeck, C.
2021. doi:10.17192/bfdm.2021.2.8340

Authentische und relevante Modellierung mit Schülerinnen und Schülern an nur einem Tag?!
Wohak, K.; Sube, M.; Schönbrodt, S.; Roeckerath, C.; Frank, M.
2021. Neue Materialien für einen realitätsbezogenen Mathematikunterricht 8 – ISTRON-Schriftenreihe. Ed.: M. Bracke, 37–50, Springer Fachmedien Wiesbaden. doi:10.1007/978-3-658-33012-5_4

Checkliste zur Unterstützung der Helmholtz-Zentren bei der Implementierung von Richtlinien für nachhaltige Forschungssoftware
Messerschmidt, R.; Pampel, H.; Bach, F.; Castell, W. zu; Denker, M.; Finke, A.; Fritzsch, B.; Hammitzsch, M.; Konrad, U.; Leifels, Y.; Möhl, C.; Nolden, M.; Scheinert, M.; Schlauch, T.; Schnicke, T.; u. a.
2021. Helmholtz Open Science Office. doi:10.48440/os.helmholtz.031

Digitales Lernmaterial zur Netflix Challenge
Schönbrodt, S.; Frank, M.
2021. Beiträge zum Mathematikunterricht 2021. Hrsg.: Kerstin Hein, Cathleen Heil, Silke Ruwisch & Susanne Prediger, WTM Verlag für wissenschaftliche Texte und Medien. doi:10.17877/DE290R-22328

Zerstörungsfreie stoffliche Beschreibung und Plausibilitätsprüfung radioaktiver Abfälle mittels QUANTOM
Coquard, L.; Nordhardt, G.; Hummel, J.; Havenith, A.; Krycki, K.; Hirsch, M.; Wangnick, M.; Fu, B.; Reisenhofer, F.; Hansmann, B.; Hansmann, T.; Helmes, C.; Dürr, M.; Rother, M.; Simons, F.; u. a.
2021. KONTEC GmbH

Punzinet
Haigh, H.; Feichtinger, P.; Inguglia, G.; Kahn, J.
2021

Punzi-loss and Punzi-net, outperforming standard MVA techniques in the search for new particles of unknown masses
Haigh, H.; Feichtinger, P.; Inguglia, G.; Kahn, J.
2021. 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021), Daejeon, Südkorea, 29. November–3. Dezember 2021

ddKS - a d-dimensional Kolmogorov-Smirnov Test
Hagen, A.; Jackson, S.; Kahn, J.; Strube, J.; Haide, I.; Pazdernik, K.; Hainje, C.
2021

Measurements of branching fractions and CP-violating charge asymmetries in multibody charmless decays reconstructed in 2019-2020 Belle II data
Belle 2 Collaboration; Abudinén, F.; Adachi, I.; Adak, R.; Adamczyk, K.; Ahlburg, P.; Ahn, J. K.; Aihara, H.; Akopov, N.; Aloisio, A.; Ameli, F.; Andricek, L.; Ky, N. A.; Asner, D. M.; Atmacan, H.; u. a.
2021

Angular analysis of decays reconstructed in 2019-2020 Belle II data
Belle 2 Collaboration; Abudinén, F.; Adachi, I.; Adak, R.; Adamczyk, K.; Ahlburg, P.; Ahn, J. K.; Aihara, H.; Akopov, N.; Aloisio, A.; Ameli, F.; Andricek, L.; Ky, N. A.; Asner, D. M.; Atmacan, H.; u. a.
2021

Punzi-loss: A non-differentiable metric approximation for sensitivity optimisation in the search for new particles
Belle 2 Collaboration; Abudinén, F.; Bertemes, M.; Bilokin, S.; Campajola, M.; Casarosa, G.; Cunliffe, S.; Corona, L.; Pietro, G. D.; Dey, S.; Eliachevitch, M.; Feichtinger, P.; Ferber, T.; Gemmler, J.; Goldenzweig, P.; u. a.
2021

Search for the decay at the Belle experiment
Belle Collaboration; Dong, T. V.; Luo, T.; Adachi, I.; Aihara, H.; Asner, D. M.; Atmacan, H.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Bahinipati, S.; Behera, P.; Belous, K.; Bernlochner, F.; u. a.
2021

Measurements of the branching fractions for decays at Belle II
Belle 2 Collaboration; Abudinén, F.; Adachi, I.; Adak, R.; Adamczyk, K.; Aggarwal, L.; Ahlburg, P.; Ahmed, H.; Ahn, J. K.; Aihara, H.; Akopov, N.; Aloisio, A.; Ameli, F.; Andricek, L.; Ky, N. A.; u. a.
2021. doi:10.5445/IR/1000140500

Search for meson decays into and missing energy with a hadronic tagging method at Belle
Belle Collaboration; Hadjivasiliou, C.; Fulsom, B. G.; Strube, J. F.; Adachi, I.; Aihara, H.; Asner, D. M.; Atmacan, H.; Aushev, T.; Babu, V.; Belous, K.; Bennett, J.; Bessner, M.; Bhardwaj, V.; Bhuyan, B.; u. a.
2021

Measurements of the branching fractions of , , and decays at Belle
Belle 2 Collaboration; Li, Y.; Cui, J. X.; Jia, S.; Shen, C. P.; Adachi, I.; Ahn, J. K.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aushev, T.; Ayad, R.; Babu, V.; Bahinipati, S.; u. a.
2021

The global and multi-annual MUSICA IASI {H2O, δD} pair dataset
Diekmann, C. J.; Schneider, M.; Ertl, B.; Hase, F.; García, O.; Khosrawi, F.; Sepúlveda, E.; Knippertz, P.; Braesicke, P.
2021. Earth system science data, 13 (11), 5273–5292. doi:10.5194/essd-13-5273-2021

Sektionskonzept Meta(daten), Terminologien und Provenienz zur Einrichtung einer Sektion im Verein Nationale Forschungsdateninfrastruktur (NFDI) e.V
Koepler, O.; Schrade, T.; Neumann, S.; Stotzka, R.; Wiljes, C.; Blümel, I.; Bracht, C.; Hamann, T.; Arndt, S.; Hunold, J.
2021. Zenodo. doi:10.5281/zenodo.5619089

Numerical database of highly-resolved turbulent flame-wall interaction simulations for model validation
Zirwes, T.; Zhang, F.; Steinhausen, M.; Habisreuther, P.; Bockhorn, H.; Hasse, C.; Trimis, D.
2021. 30. Deutscher Flammentag, Deutsche Sektion des Combustion Institutes und DVV/VDI-Gesellschaft Energie und Umwelt. Ed.: Dinkelacker, Friedrich; Pitsch Heinz; Scherer, Viktor, 1144–1153

DNS of Unsteady Flame-Wall Interaction
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Wang, R.; Suntz, R.
2021. 30. Deutscher Flammentag, Deutsche Sektion des Combustion Institutes und DVV/VDI-Gesellschaft Energie und Umwelt. Ed.: F. Dinkelacker, H. Pitsch, V. Scherer, 1106–1115

Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting
Stammer, P.; Burigo, L.; J kel, O.; Frank, M.; Wahl, N.
2021. Physics in Medicine and Biology, 66 (20), 205003. doi:10.1088/1361-6560/ac287f

Mathematische Grundlagen der Künstlichen Intelligenz im Schulunterricht: Chancen für eine Bereicherung des Unterrichts in linearer Algebra
Schönbrodt, S.; Camminady, T.; Frank, M.
2021. Mathematische Semesterberichte, 69, 73–101. doi:10.1007/s00591-021-00310-x

Mixed Precision Incomplete and Factorized Sparse Approximate Inverse Preconditioning on GPUs
Göbel, F.; Grützmacher, T.; Ribizel, T.; Anzt, H.
2021. Euro-Par 2021: Parallel Processing: 27th International Conference on Parallel and Distributed Computing, Lisbon, Portugal, September 1–3, 2021, Proceedings. Ed.: L. Sousa, 550–564, Springer-Verlag. doi:10.1007/978-3-030-85665-6_34

Retrieval of Water Vapour Profiles from GLORIA Nadir Observations
König, N.; Wetzel, G.; Höpfner, M.; Friedl-Vallon, F.; Johansson, S.; Kleinert, A.; Schneider, M.; Ertl, B.; Ungermann, J.
2021. Remote sensing, 13 (18), Article no: 3675. doi:10.3390/rs13183675

Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2021. Springer. doi:10.21203/rs.3.rs-832355/v1

Odderon Exchange from Elastic Scattering Differences between pp and pp Data at 1.96 TeV and from pp Forward Scattering Measurements
Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Alves, G. A.; Antchev, G.; Askew, A.; Aspell, P.; Assis Jesus, A. C. S.; Atanassov, I.; u. a.
2021. Physical Review Letters, 127 (6), Art.-Nr.: 062003. doi:10.1103/PhysRevLett.127.062003

Digitale Erforschung epistemischer Verflechtungen : Informationsinfrastruktur und vormoderne Wissenstransfers
Krewet, M.; Kahl, J.; Götzelmann, G.; Hübner, J.; Hegel, P.; Söring, S.; Tonne, D.
2021. Wissensoikonomien. Hrsg.: N. Schmidt, 135–150, Harrassowitz Verlag

A Collaborative Peer Review Process for Grading Coding Assignments
Nayak, P.; Göbel, F.; Anzt, H.
2021. Computational Science – ICCS 2021: 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part VI. Ed.: M. Paszynski, 654–660, Springer-Verlag. doi:10.1007/978-3-030-77980-1_49

Search for the decay B →η’η
Belle Collaboration; Nisar, N. K.; Savinov, V.; Adachi, I.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aushev, T.; Ayad, R.; Babu, V.; Bahinipati, S.; Behera, P.; Bennett, J.; Bessner, M.; u. a.
2021. Physical review / D, 104 (3), Art.-Nr.: L031101. doi:10.1103/PhysRevD.104.L031101

AI-based thermal bridge detection of building rooftops on district scale using aerial images
Mayer, Z.; Kahn, J.; Hou, Y.; Volk, R.
2021. EG-ICE 2021 Workshop on Intelligent Computing in Engineering. Ed.: Jimmy Abualdenien, André Borrmann, Lucian-Constantin Ungureanu, Timo Hartmann, 497–507, Universitätsverlag der TU Berlin

Erratum: Measurement of the CKM matrix element |V| from B → D lv at Belle [Phys. Rev. / D, vol. 100, Art.Nr. 052007, 2019; DOI: 10.1103/PhysRevD.100.052007 ]
Belle Collaboration; Waheed, E.; Urquijo, P.; Ferlewicz, D.; Adachi, I.; Adamczyk, K.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aushev, T.; Ayad, R.; Babu, V.; Badhrees, I.; Bansal, V.; u. a.
2021. Physical review / D, 103 (7), Art.Nr.: 079901. doi:10.1103/PhysRevD.103.079901

Measurement of branching fractions and CP asymmetries for D →K(η,π) and D → π(η,π) decays at Belle
Belle Collaboration; Guan, Y.; Schwartz, A. J.; Kinoshita, K.; Adachi, I.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Behera, P.; Bennett, J.; u. a.
2021. Physical review / D, 103 (11), Article: 112005. doi:10.1103/PhysRevD.103.112005

Probabilistic Representation of Objects and Their Support Relations
Paus, F.; Asfour, T.
2021. Experimental Robotics : The 17th International Symposium on Experimental Robotics, November 9–12, 2020 [postponed to Nov. 15–18, 2021], Floriana, Malta. Ed.: B. Siciliano, 510–519, Springer International Publishing. doi:10.1007/978-3-030-71151-1_45

Entropy–Based Methods for Uncertainty Quantification of Hyperbolic Conservation Laws
Frank, M.; Kusch, J.; Wolters, J.
2021. Recent Advances in Numerical Methods for Hyperbolic PDE Systems – NumHyp 2019. Ed.: M. Muñoz-Ruiz, 29–56, Springer International Publishing. doi:10.1007/978-3-030-72850-2_2

mytoken - OpenID Connect Tokens for Long-term Authorization. Masterarbeit
Zachmann, G.
2021. doi:10.5445/IR/1000134712

An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action
Anzt, H.; Bach, F.; Druskat, S.; Löffler, F.; Loewe, A.; Renard, B. Y.; Seemann, G.; Struck, A.; Achhammer, E.; Aggarwal, P.; Appel, F.; Bader, M.; Brusch, L.; Busse, C.; Chourdakis, G.; u. a.
2021. F1000Research, 9, 295. doi:10.12688/f1000research.23224.2

Numerical Solution Strategies in Permeation Processes
Weth, A. von der; Piccioni Koch, D.; Arbeiter, F.; Klimenko, D.; Schlindwein, G.; Schulz, M. J.; Pasler, M. J.; Prothmann, N.; Zinn, K.
2021. 17th International Conference on Diffusion in Solids and Liquids (DSL 2021), Valletta, Malta, 28. Juni–2. Juli 2021

A Semi-supervised Approach for Trajectory Segmentation to Identify Different Moisture Processes in the Atmosphere
Ertl, B.; Schneider, M.; Diekmann, C.; Meyer, J.; Streit, A.
2021. Computational Science – ICCS 2021 – 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part I. Ed.: M. Paszynski, 264–277, Springer International Publishing. doi:10.1007/978-3-030-77961-0_23

Evidence for X(3872)→J/ψπ+π− Produced in Single-Tag Two-Photon Interactions
Belle Collaboration; Teramoto, Y.; Uehara, S.; Masuda, M.; Adachi, I.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aushev, T.; Ayad, R.; Babu, V.; Behera, P.; Beleño, C.; Bennett, J.; u. a.
2021. Physical review letters, 126 (12), Art.-Nr.: 122001. doi:10.1103/PhysRevLett.126.122001

On GPU optimizations of stencil codes for highly parallel simulations
Pfisterer, N.; Berghoff, M.; Streit, A.
2021. Proceedings 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing PDP 2021: Valladolid, Spain ; 10-12 March 2021, 228–235, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PDP52278.2021.00043

Test of Lepton-Flavor Universality in B → K*l⁺l⁻ Decays at Belle
Belle Collaboration; Wehle, S.; Adachi, I.; Adamczyk, K.; Aihara, H.; Asner, D. M.; Atmacan, H.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Behera, P.; Berger, M.; Bhardwaj, V.; Biswal, J.; u. a.
2021. Physical review letters, 126 (16), Article: 161801. doi:10.1103/PhysRevLett.126.161801

Pollution trace gases C₂H₆, C₂H₂, HCOOH, and PAN in the North Atlantic UTLS: observations and simulations
Wetzel, G.; Friedl-Vallon, F.; Glatthor, N.; Grooß, J.-U.; Gulde, T.; Höpfner, M.; Johansson, S.; Khosrawi, F.; Kirner, O.; Kleinert, A.; Kretschmer, E.; Maucher, G.; Nordmeyer, H.; Oelhaf, H.; Orphal, J.; u. a.
2021. Atmospheric chemistry and physics, 21 (10), 8213–8232. doi:10.5194/acp-21-8213-2021

1. KIT-interner Workshop zur Wasserstoff- und Brennstoffzellen-Forschung
Weth, A. von der; Piccioni Koch, D.; Pasler, V.
2021. 1. KIT-interner Workshop zur Wasserstoff- und Brennstoffzellen-Forschung (2021), Online, 2. März 2021

Oxygen-Evolution Reaction by a Palladium Foil in the Presence of Iron
Akbari, N.; Kondov, I.; Vandichel, M.; Aleshkevych, P.; Najafpour, M. M.
2021. Inorganic Chemistry, 60 (8), 5682–5693. doi:10.1021/acs.inorgchem.0c03746

A Lagrangian perspective on stable water isotopes during the West African Monsoon
Diekmann, C. J.; Schneider, M.; Knippertz, P.; Vries, A. J. de; Pfahl, S.; Aemisegger, F.; Dahinden, F.; Ertl, B.; Khosrawi, F.; Wernli, H.; Braesicke, P.
2021. doi:10.1002/essoar.10506628.1

Application of reaction-diffusion manifolds (REDIM) for the simulation of two-dimensional axisymmetric laminar diffusion flames
Li, N.; Yu, C.; Zirwes, T.; Maas, U.
2021. 10th European Combustion Meeting (ECM 2021), April 14-15, 2021, Virtual Edition. Proceedings Volume, MCM

The MUSICA IASI {HO, δD} pair product
Diekmann, C. J.; Schneider, M.; Ertl, B.; Hase, F.; García, O.; Khosrawi, F.; Sepúlveda, E.; Knippertz, P.; Braesicke, P.
2021. Earth system science data discussions. doi:10.5194/essd-2021-87

Test of lepton flavor universality and search for lepton flavor violation in B → Kℓℓ decays
Belle Collaboration; Choudhury, S.; Sandilya, S.; Trabelsi, K.; Giri, A.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Bahinipati, S.; Behera, P.; u. a.
2021. Journal of high energy physics, 2021 (3), Art. Nr.: 105. doi:10.1007/JHEP03(2021)105

Balanced and Compressed Coordinate Layout for the Sparse Matrix-Vector Product on GPUs
Aliaga, J. I.; Anzt, H.; Quintana-Ortí, E. S.; Tomás, A. E.; Tsai, Y. M.
2021. Euro-Par 2020: Parallel Processing Workshops: Euro-Par 2020 International Workshops, Warsaw, Poland, August 24–25, 2020, Revised Selected Papers. Ed.: B. Balis, 83–95, Springer-Verlag. doi:10.1007/978-3-030-71593-9_7

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP
Tsai, Y. M.; Cojean, T.; Ribizel, T.; Anzt, H.
2021. Euro-Par 2020: Parallel Processing Workshops: Euro-Par 2020 International Workshops, Warsaw, Poland, August 24–25, 2020, Revised Selected Papers. Ed.: B. Balis, 109–121, Springer-Verlag. doi:10.1007/978-3-030-71593-9_9

RDA Metadata Standards Catalog Adoption
Hartmann, V.; Jejkal, T.; Sharfeldin, O.; Stotzka, R.
2021. 17th RDA Plenary Meeting (2021), Online, 20.–23. April 2021

Metastore - Enable FAIR Metadata Documents
Hartmann, V.; Jejkal, T.; Stotzka, R.
2021. 17th RDA Plenary Meeting (2021), Online, 20.–23. April 2021

Intercomparison of arctic XHO observations from three ground-based Fourier transform infrared networks and application for satellite validation
Tu, Q.; Hase, F.; Blumenstock, T.; Schneider, M.; Schneider, A.; Kivi, R.; Heikkinen, P.; Ertl, B.; Diekmann, C.; Khosrawi, F.; Sommer, M.; Borsdorff, T.; Raffalski, U.
2021. Atmospheric Measurement Techniques, 14 (3), 1993–2011. doi:10.5194/amt-14-1993-2021

Predictive storage strategy for optimal design of hybrid CSP-PV plants with immersion heater
Richter, P.; Trimborn, T.; Aldenhoff, L.
2021. Solar Energy, 218, 237–250. doi:10.1016/j.solener.2020.11.005

Study of the normalized transverse momentum distribution of W bosons produced in p collisions at =1.96  TeV
Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; Avila, C.; u. a.
2021. Physical review / D, 103 (1), Art. Nr.: 012003. doi:10.1103/PhysRevD.103.012003

Technical note: “Bit by bit”: a practical and general approach for evaluating model computational complexity vs. model performance
Azmi, E.; Ehret, U.; Weijs, S. V.; Ruddell, B. L.; Perdigão, R. A. P.
2021. Hydrology and earth system sciences, 25 (2), 1103–1115. doi:10.5194/hess-25-1103-2021

Crediting pull requests to open source research software as an academic contribution
Anzt, H.; Kuehn, E.; Flegar, G.
2021. Journal of computational science, 49, Art.-Nr.: 101278. doi:10.1016/j.jocs.2020.101278

Deutschland in der European Open Science Cloud
Streit, A.; Wezel, J. van
2021. Praxishandbuch Forschungsdatenmanagement. Hrsg.: Markus Putnings, 31–52, De Gruyter Saur. doi:10.1515/9783110657807-003

Accurate interpolation methods for the annual simulation of solar central receiver systems using celestial coordinate system
Richter, P.; Tinnes, J.; Aldenhoff, L.
2021. Solar energy, 213, 328–338. doi:10.1016/j.solener.2020.10.087

Identification of Flame Regimes in Partially Premixed Combustion from a Quasi-DNS Dataset
Zirwes, T.; Zhang, F.; Habisreuther, P.; Hansinger, M.; Bockhorn, H.; Pfitzner, M.; Trimis, D.
2021. Flow, turbulence and combustion, 106 (2), 373–404. doi:10.1007/s10494-020-00228-9

In-situ flame particle tracking based on barycentric coordinates for studying local flame dynamics in pulsating Bunsen flames
Zirwes, T.; Zhang, F.; Wang, Y.; Habisreuther, P.; Denev, J. A.; Chen, Z.; Bockhorn, H.; Trimis, D.
2021. Proceedings of the Combustion Institute, 38 (2), 2057–2066. doi:10.1016/j.proci.2020.07.033

Ignition of dimethyl ether/air mixtures by hot particles: Impact of low temperature chemical reactions
Wang, Y.; Zhang, H.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2021. Proceedings of the Combustion Institute, 38 (2), 2459–2466. doi:10.1016/j.proci.2020.06.254

Numerical Study of Quenching Distances for Side-Wall Quenching Using Detailed Diffusion and Chemistry
Zirwes, T.; Häber, T.; Zhang, F.; Kosaka, H.; Dreizler, A.; Steinhausen, M.; Hasse, C.; Stagni, A.; Trimis, D.; Suntz, R.; Bockhorn, H.
2021. Flow, turbulence and combustion, 106, 649–679. doi:10.1007/s10494-020-00215-0

Near Wall Dynamics of Premixed Flames
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Suntz, R.
2021. Proceedings of the Combustion Institute, 38 (2), 1955–1964. doi:10.1016/j.proci.2020.06.058

Numerical Investigation of Local Heat-Release Rates and Thermo-Chemical States in Side-Wall Quenching of Laminar Methane and Dimethyl Ether Flames
Steinhausen, M.; Luo, Y.; Popp, S.; Straßacker, C.; Zirwes, T.; Kosaka, H.; Zentgraf, F.; Maas, U.; Sadiki, A.; Dreizler, A.; Hasse, C.
2021. Flow, turbulence and combustion, 106, 681–700. doi:10.1007/s10494-020-00146-w

Numerical Computation of Turbulent Flow Fields in a Fan-stirred Combustion Bomb
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.; Trimis, D.
2021. Combustion science and technology, 193 (4), 594–610. doi:10.1080/00102202.2019.1665520

A Guide for Publishing, Using, and Licensing Research Software in Germany
Struck, A.; Loewe, A.; Achhammer, E.; Rack, F.; Bach, F.; Löffler, F.; Seemann, G.; Anzt, H.; Funk, M.; Unger, S.; Druskat, S.; Friedl, S.
2020. Zenodo. doi:10.5281/zenodo.4327148

JAWS – Just Another Workspace Suite Data Orchestration for HPC Environments
Soysal, M.
2020. The 18th Annual Meeting of the 2020 International Conference on High Performance Computing & Simulation

Erklärvideo "Ransomware als besonderen Typ betrügerischer Nachrichten erkennen"
Burgdorf, M. (Hrsg.)
2020

Erklärvideo "President Scam bzw. CEO Fraud als besonderen Typ betrügerischer Nachrichten erkennen"
Burgdorf, M. (Hrsg.)
2020

Erklärvideo "Worauf achte ich bei der Nutzung von Cloud-Diensten?"
Burgdorf, M. (Hrsg.)
2020

Erklärvideo "Wie nutze ich Soziale Netzwerke?"
Burgdorf, M. (Hrsg.)
2020

Erklärvideo "Was ist Social Engineering und wie erkenne ich es?"
Burgdorf, M. (Hrsg.)
2020

The Repository Chemotion: Infrastructure for Sustainable Research in Chemistry
Tremouilhac, P.; Lin, C.-L.; Huang, P.-C.; Huang, Y.-C.; Nguyen, A.; Jung, N.; Bach, F.; Ulrich, R.; Neumair, B.; Streit, A.; Bräse, S.
2020. Angewandte Chemie / International edition, 59 (50), 22771–22778. doi:10.1002/anie.202007702

Erklärvideo "Wie schütze ich unterwegs oder auf Geschäftsreise meine Informationen?"
Burgdorf, M. (Hrsg.)
2020

Erklärvideo "Wie schütze ich meine Daten rund um den Arbeitsplatz?"
Burgdorf, M. (Hrsg.)
2020

Erklärvideo "Wie erstelle ich mir ein komplexes Passwort?"
Burgdorf, M. (Hrsg.)
2020

Pollution trace gas distributions and their transport in the Asian monsoon upper troposphere and lowermost stratosphere during the StratoClim campaign 2017
Johansson, S.; Höpfner, M.; Kirner, O.; Wohltmann, I.; Bucci, S.; Legras, B.; Friedl-Vallon, F.; Glatthor, N.; Kretschmer, E.; Ungermann, J.; Wetzel, G.
2020. Atmospheric chemistry and physics, 20 (23), 14695–14715. doi:10.5194/acp-20-14695-2020

Erklärvideo "Warum betrifft mich das Thema Informationssicherheit?"
Burgdorf, M. (Hrsg.)
2020

Non-stationary spatial regression for modelling monthly precipitation in Germany
Marques, I.; Klein, N.; Kneib, T.
2020. Spatial Statistics, 40, Art.-Nr.: 100386. doi:10.1016/j.spasta.2019.100386

Extending an Open-Source Federated Identity Management System for Enhanced HPC Security
Buchmüller, J.; Raffeiner, S.; Simon, M.; Obermaier, H.; Weisbrod, P.; Weiß, U.; Nußbaumer, M.
2020, November 17. The International Conference for High Performance Computing, Networking, Storage, and Analysis (2020, SC20 2020), Online, 9.–19. November 2020

Including residual contact information into replica-exchange MD simulations significantly enriches native-like conformations
Voronin, A.; Weiel, M.; Schug, A.
2020. PLOS ONE, 15 (11), Art.-Nr.: e0242072. doi:10.1371/journal.pone.0242072

Spatio-temporal Structure of the Boundary Layer under the Impact of Mountain Waves
Kalthoff, N.; Adler, B.; Bischoff-Gauss, I.
2020. Meteorologische Zeitschrift, 29 (5), 409–424. doi:10.1127/metz/2020/1033

Workflow Generation with wfGenes
Roozmeh, M.; Kondov, I.
2020. IEEE/ACM Workflows in Support of Large-Scale Science (WORKS), 9–16, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WORKS51914.2020.00007

On the role of trend and variability in the hydroxyl radical (OH) in the global methane budget
Zhao, Y.; Saunois, M.; Bousquet, P.; Lin, X.; Berchet, A.; Hegglin, M. I.; Canadell, J. G.; Jackson, R. B.; Deushi, M.; Jöckel, P.; Kinnison, D.; Kirner, O.; Strode, S.; Tilmes, S.; Dlugokencky, E. J.; u. a.
2020. Atmospheric chemistry and physics, 20 (21), 13011–13022. doi:10.5194/acp-20-13011-2020

Effective Dynamic Integration and Utilization of Heterogenous Compute Resources
Fischer, M.; Giffels, M.; Heiss, A.; Kuehn, E.; Schnepf, M.; Cube, R. F. von; Petzold, A.; Quast, G.
2020. The European physical journal / Web of Conferences, 245, Article no: 07038. doi:10.1051/epjconf/202024507038

Lightweight dynamic integration of opportunistic resources
Fischer, M.; Kuehn, E.; Giffels, M.; Schnepf, M. J.; Petzold, A.; Heiss, A.
2020. The European physical journal / Web of Conferences, 245, Article no: 07040. doi:10.1051/epjconf/202024507040

Setup and commissioning of a high-throughput analysis cluster
Caspart, R.; Fischer, M.; Giffels, M.; Cube, R. F. von; Heidecker, C.; Kuehn, E.; Quast, G.; Heiss, A.; Petzold, A.
2020. (C. Doglioni, D. Kim, G. A. Stewart, L. Silvestris, P. Jackson & W. Kamleh, Hrsg.) The European physical journal / Web of Conferences, 245, Article no: 07007. doi:10.1051/epjconf/202024507007

Ray Effect Mitigation for the Discrete Ordinates Method Using Artificial Scattering
Frank, M.; Kusch, J.; Camminady, T.; Hauck, C. D.
2020. Nuclear science and engineering, 194 (11), 971–988. doi:10.1080/00295639.2020.1730665

Numerical evaluation of a novel double-concentric swirl burner for sulfur combustion
Zhang, F.; Heidarifatasmi, H.; Harth, S.; Zirwes, T.; Wang, R.; Fedoryk, M.; Sebbar, N.; Habisreuther, P.; Trimis, D.; Bockhorn, H.
2020. Renewable & sustainable energy reviews, 133, Art. Nr.: 110257. doi:10.1016/j.rser.2020.110257

Intrusive acceleration strategies for uncertainty quantification for hyperbolic systems of conservation laws
Kusch, J.; Wolters, J.; Frank, M.
2020. Journal of computational physics, 419, Art. Nr.: 109698. doi:10.1016/j.jcp.2020.109698

Deep Learning, Feature Learning, and Clustering Analysis for SEM Image Classification
Aversa, R.; Coronica, P.; De Nobili, C.; Cozzini, S.
2020. Data Intelligence, 2 (4), 513–528. doi:10.1162/dint_a_00062

Cells in Silico – introducing a high-performance framework for large-scale tissue modeling
Berghoff, M.; Rosenbauer, J.; Hoffmann, F.; Schug, A.
2020. BMC bioinformatics, 21 (1), 436. doi:10.1186/s12859-020-03728-7

Robust Mathematical Formulation and Probabilistic Description of Agent-Based Computational Economic Market Models
Beikirch, M.; Cramer, S.; Frank, M.; Otte, P.; Pabich, E.; Trimborn, T.
2020. Advances in Complex Systems, 23 (6), Art.-Nr.: 2050017. doi:10.1142/S0219525920500174

The Eulerian Stochastic Fields Method Applied to Large Eddy Simulations of a Piloted Flame with Inhomogeneous Inlet
Hansinger, M.; Zirwes, T.; Zips, J.; Pfitzner, M.; Zhang, F.; Habisreuther, P.; Bockhorn, H.
2020. Flow, turbulence and combustion, 105 (3), 837–867. doi:10.1007/s10494-020-00159-5

Numerical Simulations of Turbulent Flame Propagation in a Fan-Stirred Combustion Bomb and Bunsen-Burner at Elevated Pressure
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.; Trimis, D.
2020. Flow, turbulence and combustion, 106, 925–944. doi:10.1007/s10494-020-00209-y

Candidate-gene association analysis for a continuous phenotype with a spike at zero using parent-offspring trios
Klein, N.; Entwistle, A.; Rosenberger, A.; Kneib, T.; Bickeböller, H.
2020. Journal of Applied Statistics, 47 (11), 2066–2080. doi:10.1080/02664763.2019.1704226

A velocity-space adaptive unified gas kinetic scheme for continuum and rarefied flows
Xiao, T.; Liu, C.; Xu, K.; Cai, Q.
2020. Journal of computational physics, 415, Art. Nr.: 109535. doi:10.1016/j.jcp.2020.109535

A customized precision format based on mantissa segmentation for accelerating sparse linear algebra
Grützmacher, T.; Cojean, T.; Flegar, G.; Göbel, F.; Anzt, H.
2020. Concurrency and computation, 32 (15), Article: e5418. doi:10.1002/cpe.5418

Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning
Rall, D.; Schweidtmann, A. M.; Kruse, M.; Evdochenko, E.; Mitsos, A.; Wessling, M.
2020. Journal of Membrane Science, 608, Art.-Nr.: 118208. doi:10.1016/j.memsci.2020.118208

Detecting Regime Transitions of the Nocturnal and Polar Near-Surface Temperature Inversion
Kaiser, A.; Faranda, D.; Krumscheid, S.; Belušić, D.; Vercauteren, N.
2020. Journal of the Atmospheric Sciences, 77 (8), 2921–2940. doi:10.1175/JAS-D-19-0287.1

Quantifying uncertain system outputs via the multilevel Monte Carlo method. Part I: Central moment estimation
Krumscheid, S.; Nobile, F.; Pisaroni, M.
2020. Journal of Computational Physics, 414, Article no: 109466. doi:10.1016/j.jcp.2020.109466

HeAT – a Distributed and GPU-accelerated Tensor Framework for Data Analytics
Götz, M.; Coquelin, D.; Debus, C.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. doi:10.5445/IR/1000123473

Analyse verteilter Daten unter Berücksichtigung von Korrektheit, Skalierbarkeit und Vertraulichkeit. Dissertation
Schlitter, N.
2020, Juli 23. Karlsruher Institut für Technologie (KIT)

Design and Implementation of the first Generic Archive Storage Service for Research Data in Germany
Bach, F.; Schembera, B.; Van Wezel, J.
2020. International Journal of Digital Curation, 15 (1). doi:10.2218/ijdc.v15i1.553

Realizability-preserving discretization strategies for hyperbolic and kinetic equations with uncertainty. Dissertation
Kusch, J.
2020, Juli 14. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000121168

On relaxation systems and their relation to discrete velocity Boltzmann models for scalar advection–diffusion equations
Simonis, S.; Frank, M.; Krause, M. J.
2020. Philosophical transactions of the Royal Society of London / A, 378 (2175), Article: 20190400. doi:10.1098/rsta.2019.0400

NFDI4Chem - Towards a National Research Data Infrastructure for Chemistry in Germany
Steinbeck, C.; Koepler, O.; Bach, F.; Herres-Pawlis, S.; Jung, N.; Liermann, J. C.; Neumann, S.; Razum, M.; Baldauf, C.; Biedermann, F.; Bocklitz, T. W.; Boehm, F.; Broda, F.; Czodrowski, P.; Engel, T.; u. a.
2020. Research ideas and outcomes, (6), e55852, 1–100. doi:10.3897/rio.6.e55852

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP
Tsai, Y. M.; Cojean, T.; Ribizel, T.; Anzt, H.
2020. doi:10.5445/IR/1000131542

DEEP framework for deep learning
Alic, A. S.; Antonacci, M.; Caballer, M.; Campos, I.; Costantini, A.; David, M.; Dlugolinsky, S.; Donvito, G.; Gomes, J.; Hardt, M.; Heredia, I.; Hluchy, L.; Ito, K.; Kozlov, V.; Lloret, L.; u. a.
2020, Juni 23. ISC High Performance (2020), Online, 22.–25. Juni 2020

Directional bivariate quantiles: a robust approach based on the cumulative distribution function
Klein, N.; Kneib, T.
2020. AStA Advances in Statistical Analysis, 104 (2), 225–260. doi:10.1007/s10182-019-00355-3

Robust optimal aiming strategies in central receiver systems
Kuhnke, S.; Richter, P.; Kepp, F.; Cumpston, J.; Koster, A. M. C. A.; Büsing, C.
2020. Renewable energy, 152, 198–207. doi:10.1016/j.renene.2019.11.118

Cold War spy satellite images reveal long-term declines of a philopatric keystone species in response to cropland expansion
Munteanu, C.; Kamp, J.; Nita, M. D.; Klein, N.; Kraemer, B. M.; Müller, D.; Koshkina, A.; Prishchepov, A. V.; Kuemmerle, T.
2020. Proceedings of the Royal Society B: Biological Sciences, 287 (1927), 20192897. doi:10.1098/rspb.2019.2897

Optimization of Procedure for Determining Chlorine Nitrate in the Atmosphere from Ground-Based Spectroscopic Measurements
Virolainen, Y. A.; Polyakov, A. V.; Kirner, O.
2020. Journal of applied spectroscopy, 87 (2), 319–325. doi:10.1007/s10812-020-01002-5

DEEP demo: Deep learning in a Cloud and HPC environment
Kozlov, V.; Lloret, L.
2020, Mai 20. EOSC-hub week (2020), Online, 18.–20. Mai 2020

Performance gains in an ESM using parallel ad-hoc file systems
Versick, S.; Kirner, O.; Meyer, J.; Obermaier, H.; Soysal, M.
2020, April 30. doi:10.5194/egusphere-egu2020-18121

FIM4R Position Paper on the Desired Evolution of EOSC Authentication and Authorisation Infrastructures
Stevanovic, U.; Short, H.; Kesley, D.; Neilsson, I.; Gietz, P.
2020. Zenodo. doi:10.5281/zenodo.3727546

V-FOR-WaTer – the virtual research environment to discover and analyse environmental data
Meyer, J.; Azmi, E.; Hassler, S. K.; Mälicke, M.; Strobl, M.; Zehe, E.
2020. E-Science-Tage 2019: Data to Knowledge. Ed.: V. Heuveline, 199–201, Heidelberger E-Books (heiBOOKS). doi:10.11588/heibooks.598.c8434

Massively Parallel Large-Scale Multi-Model Simulation of Tumour Development Including Treatments
Berghoff, M.; Rosenbauer, J.; Schug, A.
2020. NIC Symposium 2020 : [27-28 February 2020], 63–71, Forschungszentrum Jülich

Modelling regional patterns of inefficiency: A Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales
Klein, N.; Herwartz, H.; Kneib, T.
2020. Journal of Econometrics, 214 (2), 513–539. doi:10.1016/j.jeconom.2019.07.003

Multiscale Tissue Modeling Reveals Impact of Cancer Treatment to Tumor Heterogeneity
Rosenbauer, J.; Berghoff, M.; Schug, A. H.
2020. Biophysical journal, 118 (3), 348a. doi:10.1016/j.bpj.2019.11.2006

Measurement of the integrated luminosity of the Phase 2 data of the Belle II experiment
Belle 2 Collaboration; Abudinén, F.; Adachi, I.; Ahlburg, P.; Aihara, H.; Akopov, N.; Aloisio, A.; Ameli, F.; Andricek, L.; Anh Ky, N.; Asner, D. M.; Atmacan, H.; Aushev, T.; Aushev, V.; Aziz, T.; u. a.
2020. Chinese physics / C, 44 (2), Article: 021001. doi:10.1088/1674-1137/44/2/021001

High-performance data analytics of hybrid rocket fuel combustion data using different machine learning approaches
Debus, C.; Ruettgers, A.; Petrarolo, A.; Kobald, M.; Siggel, M.
2020. AIAA Scitech 2020 Forum, American Institute of Aeronautics and Astronautics. doi:10.2514/6.2020-1161

A Cloud-Based Framework for Machine Learning Workloads and Applications
Lopez Garcia, A.; Tran, V.; Alic, A. S.; Caballer, M.; Plasencia, I. C.; Costantini, A.; Dlugolinsky, S.; Duma, D. C.; Donvito, G.; Gomes, J.; Heredia Cacha, I.; De Lucas, J. M.; Ito, K.; Kozlov, V. Y.; Nguyen, G.; u. a.
2020. IEEE access, 8, 18681–18692. doi:10.1109/ACCESS.2020.2964386

Multivariate Conditional Transformation Models
Kneib, T.; Klein, N.; Hothorn, T.
2020. Proceedings of the 35th International Workshop on Statistical Modelling. Ed.: I. Irigoien, 131–136, Universidad del País Vasco

Enhanced variable selection for distributional regression
Strömer, A.; Weinhold, L.; Staerk, C.; Titze, S.; Klein, N.; Mayr, A.
2020. Proceedings of the 35th International Workshop on Statistical Modelling. Ed.: I. Irigoien, 233–237, Universidad del Pais Vasco

Introducing non-stationarity to wrapped Gaussian spatial responses with an application to wind direction
Marques, I.; Klein, N.; Kneib, T.
2020. Proceedings of the 35th International Workshop on Statistical Modelling. Ed.: I. Irigoien, 159–164, Universidad del País Vasco

Bayesian mixed binary-continuous copula regression with an application to childhood undernutrition
Klein, N.; Kneib, T.; Marra, G.; Radice, R.
2020. Flexible Bayesian Regression Modelling, 121–152, Elsevier. doi:10.1016/B978-0-12-815862-3.00011-1

Mixed discrete‐continuous regression—A novel approach based on weight functions
Michaelis, P.; Klein, N.; Kneib, T.
2020. Stat, 9 (1), Art.-Nr.: e277. doi:10.1002/sta4.277

Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
Bach, P.; Wallisch, C.; Klein, N.; Hafermann, L.; Sauerbrei, W.; Steyerberg, E. W.; Heinze, G.; Rauch, G.
2020. (R. Bender, Hrsg.) PLOS ONE, 15 (12), e0241427. doi:10.1371/journal.pone.0241427

The GridKa Tape Storage: various performance test results and current improvements
Musheghyan, H.; Petzold, A.; Heiss, A.; Ressmann, D.; Beitzinger, M.
2020. EPJ Web of Conferences, 245, Art.-Nr.: 04026. doi:10.1051/epjconf/202024504026

bwDIM - Data In Motion
Bach, F.; Ulrich, R.
2020. E-Science-Tage 2019: Data to Knowledge (2019), Heidelberg, Deutschland, 27.–29. März 2019

bwDIM - Data In Motion
Bach, F.; Ulrich, R.
2020. E-Science-Tage 2019: Data to Knowledge. Hrsg.: V. Heuveline, 248–249, Universitätsbibliothek Heidelberg. doi:10.11588/heidok.00026842

SuLMaSS - Sustainable Lifecycle Management for Scientific Software
Loewe, A.; Seemann, G.; Wülfers, E. M.; Huang, Y.-L.; Sánchez, J.; Bach, F.; Ulrich, R.; Selzer, M.
2020. E-Science-Tage 2019: Data to Knowledge (2019), Heidelberg, Deutschland, 27.–29. März 2019

SuLMaSS - Sustainable Lifecycle Management for Scientific Software
Loewe, A.; Seemann, G.; Wülfers, E. M.; Huang, Y.-L.; Sánchez, J.; Bach, F.; Ulrich, R.; Selzer, M.
2020. E-Science-Tage 2019 : data to knowledge. Hrsg.: V. Heuveline, 238–240, Universitätsbibliothek Heidelberg

Bedarfsgerechte Weiterentwicklung von RADAR als Forschungsdaten-Repositorium für das KIT
Bach, F.; Soltau, K.; Razum, M.
2020. E-Science-Tage 2019: Data to Knowledge. Hrsg.: V. Heuveline, 162–172, Universitätsbibliothek Heidelberg

HeAT - A Distributed and GPU-accelerated Tensor Framework for Data Analytics
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data): 10-13 December 2020, online, 276–287, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData50022.2020.9378050

Studies of X(3872) and ψ(2S) production in collisions at 1.96 TeV
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2020

Studies of X(3872) and ψ(2S) production in collisions at 1.96 TeV
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2020. Physical review / D, 102 (7), Art.-Nr.: 072005. doi:10.1103/PhysRevD.102.072005

X-CEL: A Method to Estimate Near-Memory Acceleration Potential in Tile-Based MPSoCs
Rheindt, S.; Fried, A.; Lenke, O.; Nolte, L.; Sabirov, T.; Twardzik, T.; Wild, T.; Herkersdorf, A.
2020. Architecture of Computing Systems – ARCS 2020 – 33rd International Conference, Aachen, Germany, May 25–28, 2020, Proceedings. Ed.: A. Brinkmann, 109–123, Springer International Publishing. doi:10.1007/978-3-030-52794-5_9

Sparse Linear Algebra on AMD and NVIDIA GPUs – The Race Is On
Tsai, Y. M.; Cojean, T.; Anzt, H.
2020. High Performance Computing – 35th International Conference, ISC High Performance 2020, Frankfurt/Main, Germany, June 22–25, 2020, Proceedings. Ed.: P. Sadayappan, 309–327, Springer International Publishing. doi:10.1007/978-3-030-50743-5_16

IPv6-only networking on WLCG
Babik, M.; Bly, M.; Chown, T.; Christidis, D.; Chudoba, J.; Condurache, C.; Finnern, T.; Froy, T.; Grigoras, C.; Hafeez, K.; Hoeft, B.; Kelsey, D.; Lopes, R.; López Muñoz, F.; Martelli, E.; u. a.
2020. The European physical journal / Web of Conferences, 245, Art.-Nr.: 07045. doi:10.1051/epjconf/202024507045

Unroutable Traffic: Maintaining Trust and Integrity of the LHC Open Network Environment
Hoeft, B.; Ambroj Pérez, S.; Bergroth, M.; O’Connor, M.; Cziva, R.
2020. The European physical journal / Web of Conferences, 245, Art.-Nr.: 07018. doi:10.1051/epjconf/202024507018

NFDI4Ing - the National Research Data Infrastructure for Engineering Sciences
Schmitt, R. H.; Anthofer, V.; Auer, S.; Başkaya, S.; Bischof, C.; Bronger, T.; Claus, F.; Cordes, F.; Demandt, É.; Eifert, T.; Flemisch, B.; Fuchs, M.; Fuhrmans, M.; Gerike, R.; Gerstner, E.-M.; u. a.
2020. Zenodo. doi:10.5281/zenodo.4015201

Predicting resource usage for enhanced job scheduling for opportunistic resources in HEP
Kuehn, E.; Fischer, M.; Lange, S.; Petzold, A.; Heiss, A.
2020. The European physical journal / Web of Conferences, 245, Article no: 07039. doi:10.1051/epjconf/202024507039

Development of an Openfoam Solver for Numerical Simulation of Carbonization of Biomasses in Rotary Kilns
Tavakkol, S.; Zirwes, T.; Denev, J. A.; Jamshidi, F.; Bockhorn, H.
2020. OpenFOAM Workshop, June 22 - 25, 2020, Arlington, Virginia, USA

Aristoteles annotieren - Vom Handschriftendigitalisat zur qualitativ-quantitativen Annotation
Götzelmann, G.; Tonne, D.
2020. Bilddaten in den Digitalen Geisteswissenschaften. Hrsg.: C. Hastik, 53–66, Harrassowitz Verlag

Validation study for Large-Eddy Simulation of Forest Flow
Pitchurov, G.; Gromke, C.; Denev, J. A.; Cesar Cunha Galeazzo, F.
2020. E3S Web of Conferences, 207, Art.-Nr.: 02010. doi:10.1051/e3sconf/202020702010

Design of Metal-Organic Framework Templated Materials Using High-Throughput Computational Screening
Ahmad, M.; Luo, Y.; Wöll, C.; Tsotsalas, M.; Schug, A.
2020. Molecules, 25 (21), 4875. doi:10.3390/molecules25214875

Structure and properties of MgB2bulks: Ab-initio simulations compared to experiment
Romaka, V. V.; Prikhna, T. A.; Eisterer, M.; Shapovalov, A. P.; Goldacker, W.; Moshchil, V. E.; Kozyrev, A.; Rindfleisch, M.; Tompsic, M.; Hellstrom, E. E.; Grechnev, G. E.; Zhang, V. S.; Yang, F.; Li, C.
2020. IOP conference series / Materials science and engineering, 756 (1), Art. Nr.: 012020. doi:10.1088/1757-899X/756/1/012020

Loss Scheduling for Class-Imbalanced Segmentation Problems
Taubert, O.; Götz, M.; Schug, A.; Streit, A.
2020. 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 422–427, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICMLA51294.2020.00073

HeAT – a Distributed and GPU-accelerated TensorFramework for Data Analytics
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data), 276–287, Institute of Electrical and Electronics Engineers (IEEE)

Walltime Prediction and Its Impact on Job Scheduling Performance and Predictability
Klusáček, D.; Soysal, M.
2020. Job Scheduling Strategies for Parallel Processing. Ed.: D. Klusáček, 127–144, Springer

ADA-FS - Advanced Data Placement via Ad hoc File Systems at Extreme Scales
Oeste, S.; Vef, M.-A.; Soysal, M.; Nagel, W. E.; Brinkmann, A.; Streit, A.
2020. Software for Exascale Computing-SPPEXA 2016-2019. Ed.: H.-J. Bungartz, 29–59, Springer. doi:10.1007/978-3-030-47956-5_4

CoExDBSCAN: Density-based Clustering with Constrained Expansion
Ertl, B.; Meyer, J.; Schneider, M.; Streit, A.
2020. Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Ed.: A. Fred. Vol. 1, 104–115, SciTePress. doi:10.5220/0010131201040115

The whole is greater than the sum of its parts analyzing aristotle commentaries in collaboration between philology and data science
Krewet, M.; Tonne, D.; Götzelmann, G.; Hegel, P.; Soring, S.
2020. Twin Talks: Understanding and Facilitating Collaboration in Digital Humanities 2020: Proceedings of the Twin Talks 2 and 3 Workshops at DHN 2020 and DH 2020. Ed.: S. Krauwer, 103–114, RWTH Aachen

Using HEP experiment workflows for the benchmarking and accounting of WLCG computing resources
Valassi, A.; Alef, M.; Barbet, J.-M.; Datskova, O.; De Maria, R.; Fontes Medeiros, M.; Giordano, D.; Grigoras, C.; Hollowell, C.; Javurkova, M.; Khristenko, V.; Lange, D.; Michelotto, M.; Rinaldi, L.; Sciabà, A.; u. a.
2020. The European physical journal / Web of Conferences, 245, Art.-Nr.: 07035. doi:10.1051/epjconf/202024507035

Adaptive clustering: reducing the computational costs of distributed (hydrological) modelling by exploiting time-variable similarity among model elements
Ehret, U.; Pruijssen, R. van; Bortoli, M.; Loritz, R.; Azmi, E.; Zehe, E.
2020. Hydrology and earth system sciences, 24 (9), 4389–4411. doi:10.5194/hess-24-4389-2020

Evaluating asynchronous Schwarz solvers on GPUs
Nayak, P.; Cojean, T.; Anzt, H.
2020

Modeling of Wnt-mediated tissue patterning in vertebrate embryogenesis
Rosenbauer, J.; Zhang, C.; Mattes, B.; Reinartz, I.; Wedgwood, K.; Schindler, S.; Sinner, C.; Scholpp, S.; Schug, A.
2020. (A. R. Asthagiri, Hrsg.) PLoS Computational Biology, 16 (6), e1007417. doi:10.1371/journal.pcbi.1007417

Evolutionary Approach of Clustering to Optimize Hydrological Simulations
Azmi, E.; Strobl, M.; Pruijssen, R. van; Ehret, U.; Meyer, J.; Streit, A.
2020. Computational Science and Its Applications – ICCSA 2020 – 20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part I. Ed.: O. Gervasi, 617–633, Springer. doi:10.1007/978-3-030-58799-4_45

DNS-studies on flame front markers for turbulent premixed combustion
Schieβl R.; Denev, J. A.
2020. Combustion theory and modelling, 24 (6), 983–1001. doi:10.1080/13647830.2020.1800102

Multiprecision Block-Jacobi for iterative triangular solves
Goebel, F.; Anzt, H.; Cojean, T.; Flegar, G.; Quintana-Ortí, E. S.
2020. Lecture notes in computer science, 546–560, Springer. doi:10.1007/978-3-030-57675-2_34

Annotationen und ihre infrastrukturellen Prämissen
Hegel, P.; Götzelmann, G.; Krewet, M.; Tonne, D.
2020. Digital Humanities Austria 2018 : Empowering Researchers. Hrsg.: M. Ernst, 150–153, Austrian Academy of Sciences Press. doi:10.1553/dha-proceedings2018s1

DHd 2020 Spielräume: Digital Humanities zwischen Modellierung und Interpretation. Konferenzabstracts
Schöch, C.
2020. Zenodo. doi:10.5281/zenodo.3666690

Volltexte – die Zukunft alter Drucke: Bericht zum Abschlussworkshop des OCR-D-Projekts
Engl, E.; Boenig, M.; Baierer, K.; Hartmann, V.; Neudecker, C.
2020. O-bib, 7 (2), 1–4. doi:10.5282/O-BIB/5600

A low-rank method for two-dimensional time-dependent radiation transport calculations
Peng, Z.; McClarren, R. G.; Frank, M.
2020

Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence
Amos, M.; Young, P. J.; Hosking, J. S.; Lamarque, J.-F.; Abraham, N. L.; Akiyoshi, H.; Archibald, A. T.; Bekki, S.; Deushi, M.; Jöckel, P.; Kinnison, D.; Kirner, O.; Kunze, M.; Marchand, M.; Plummer, D. A.; u. a.
2020. Atmospheric chemistry and physics, 20 (16), 9961–9977. doi:10.5194/acp-20-9961-2020

A low-rank method for two-dimensional time-dependent radiation transport calculations
Peng, Z.; McClarren, R. G.; Frank, M.
2020. Journal of computational physics, 421, Art.-Nr.: 109735. doi:10.1016/j.jcp.2020.109735

Oxygen Evolution and Reduction on Fe-doped NiOOH: Influence of Solvent, Dopant Position and Reaction Mechanism
Vandichel, M.; Laasonen, K.; Kondov, I.
2020. Topics in catalysis, 63, 833–845. doi:10.1007/s11244-020-01334-8

Federation of compute resources available to the German CMS community
Cube, R. F. von; Giffels, M.; Heidecker, C.; Quast, G.; Sauter, M. B.; Schnepf, M. J.
2020. Journal of physics / Conference series, 1525 (1), Art. Nr.: 012055. doi:10.1088/1742-6596/1525/1/012055

Boosting Performance of Data-intensive Analysis Workflows with Distributed Coordinated Caching
Heidecker, C.; Cube, R. F. von; Giffels, M.; Quast, G.; Sauter, M.; Schnepf, M. J.
2020. Journal of physics / Conference series, 1525 (1), Art. Nr.: 012065. doi:10.1088/1742-6596/1525/1/012065

HEP Analyses on Dynamically Allocated Opportunistic Computing Resources
Schnepf, M. J.; Cube, R. F. von; Heidecker, C.; Fischer, M.; Giffels, M.; Kuehn, E.; Heiss, A.; Petzold, A.; Quast, G.; Sauter, M.
2020. Journal of physics / Conference series, 1525 (1), Art. Nr.: 012067. doi:10.1088/1742-6596/1525/1/012067

Emerging Tumor Development by Simulating Single-cell Events [submitted]
Rosenbauer, J.; Berghoff, M.; Schug, A.
2020. bioRxiv beta. doi:10.1101/2020.08.24.264150

Pax6 organizes the anterior eye segment by guiding two distinct neural crest waves
Takamiya, M.; Stegmaier, J.; Kobitski, A. Y.; Schott, B.; Weger, B. D.; Margariti, D.; Cereceda Delgado, A. R.; Gourain, V.; Scherr, T.; Yang, L.; Sorge, S.; Otte, J. C.; Hartmann, V.; Wezel, J. van; Stotzka, R.; u. a.
2020. PLoS Genetics, 16 (6), Art. Nr.: e1008774. doi:10.1371/journal.pgen.1008774

An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action
Anzt, H.; Bach, F.; Druskat, S.; Löffler, F.; Loewe, A.; Renard, B. Y.; Seemann, G.; Struck, A.; Achhammer, E.; Aggarwal, P.; Appel, F.; Bader, M.; Brusch, L.; Busse, C.; Chourdakis, G.; u. a.
2020. F1000Research, 9, Article no: 295. doi:10.12688/f1000research.23224.1

Evaluating DCA-based method performances for RNA contact prediction by a well-curated data set
Pucci, F.; Zerihun, M. B.; Peter, E. K.; Schug, A.
2020. RNA, 26 (7), 794–802. doi:10.1261/rna.073809.119

Pcdh18a regulates endocytosis of E-cadherin during axial mesoderm development in zebrafish
Bosze, B.; Ono, Y.; Mattes, B.; Sinner, C.; Gourain, V.; Thumberger, T.; Tlili, S.; Wittbrodt, J.; Saunders, T. E.; Strähle, U.; Schug, A.; Scholpp, S.
2020. Histochemistry and cell biology, 154, 463–480. doi:10.1007/s00418-020-01887-5

Massively Parallel Stencil Strategies for Radiation Transport Moment Model Simulations
Berghoff, M.; Frank, M.; Seibold, B.
2020. Computational Science – ICCS 2020 : 20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020. Proceedings. Part 7. Ed.: V. Krzhizhanovskaya, 242–256, Springer Nature. doi:10.1007/978-3-030-50436-6_18

Load-balancing Sparse Matrix Vector Product Kernels on GPUs
Anzt, H.; Cojean, T.; Yen-Chen, C.; Dongarra, J.; Flegar, G.; Nayak, P.; Tomov, S.; Tsai, Y. M.; Wang, W.
2020. ACM Transactions on Parallel Computing, 7 (1), Article: 2. doi:10.1145/3380930

Acceleration of PageRank with Customized Precision Based on Mantissa Segmentation
Grützmacher, T.; Cojean, T.; Flegar, G.; Anzt, H.; Quintana-Ortí, E. S.
2020. ACM Transactions on Parallel Computing, 7 (1), Article: 4. doi:10.1145/3380934

pydca v1.0: a comprehensive software for direct coupling analysis of RNA and protein sequences
Zerihun, M. B.; Pucci, F.; Peter, E. K.; Schug, A.
2020. Bioinformatics, 36 (7), 2264–2265. doi:10.1093/bioinformatics/btz892

Theoretical background of the hybrid VπLES method for flows with variable transport properties
Kornev, N.; Denev, J.; Samarbakhsh, S.
2020. Fluids, 5 (2), Article: 45. doi:10.3390/fluids5020045

Alea – Complex Job Scheduling Simulator
Klusáček, D.; Soysal, M.; Suter, F.
2020. Parallel Processing and Applied Mathematics - 13th International Conference, PPAM 2019, Bialystok, Poland, September 8–11, 2019, Revised Selected Papers, Part II. Hrsg.: R. Wyrzykowski, 217–229, Springer International Publishing. doi:10.1007/978-3-030-43222-5_19

Computational Study on Small Pt Clusters: Structure of Pt Clusters and Elementary Steps in Nanocatalysis. Dissertation
Yohannes, A. G.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000105273

Compression Methods for Structured Floating-Point Data and their Application in Climate Research. Dissertation
Çayoğlu, U.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000105055

Filtered stochastic Galerkin methods for hyperbolic equations
Kusch, J.; McClarren, R. G.; Frank, M.
2020. Journal of computational physics, 403, Article No.109073. doi:10.1016/j.jcp.2019.109073

Quasi-DNS Dataset of a Piloted Flame with Inhomogeneous Inlet Conditions
Zirwes, T.; Zhang, F.; Habisreuther, P.; Hansinger, M.; Bockhorn, H.; Pfitzner, M.; Trimis, D.
2020. Flow, turbulence and combustion, 104, 997–1027. doi:10.1007/s10494-019-00081-5

A structured approach to the construction of stable linear Lattice Boltzmann collision operator
Otte, P.; Frank, M.
2020. Computers and mathematics with applications, 79 (5), 1447–1460. doi:10.1016/j.camwa.2019.09.009

Belle II pixel detector: Performance of final DEPFET modules
Paschen, B.; Abudinen, F.; Ackermann, K.; Ahlburg, P.; Albalawi, M.; Alonso, O.; Andricek, L.; Ayad, R.; Babu, V.; Bai, Y.; Bilka, T.; Blanco, R.; Boronat, M.; Bozek, A.; Camien, C.; u. a.
2020. (Collaboration, PXD, Hrsg.) Nuclear instruments & methods in physics research / A, 958, Article No.162222. doi:10.1016/j.nima.2019.05.063

diSTruct v1.0: generating biomolecular structures from distance constraints
Taubert, O.; Reinartz, I.; Meyerhenke, H.; Schug, A.
2019. Bioinformatics, 35 (24), 5337–5338. doi:10.1093/bioinformatics/btz578

Implicit Copulas from Bayesian Regularized Regression Smoothers
Klein, N.; Smith, M. S.
2019. Bayesian Analysis, 14 (4), 1143–1171. doi:10.1214/18-BA1138

Concentration dependent energy levels shifts in donor-acceptor mixtures due to intermolecular electrostatic interaction
Bag, S.; Friederich, P.; Kondov, I.; Wenzel, W.
2019. Scientific reports, 9 (1), Art. Nr.: 12424. doi:10.1038/s41598-019-48877-9

Assessing the relationship between markers of glycemic control through flexible copula regression models
Espasandín-Domínguez, J.; Cadarso-Suárez, C.; Kneib, T.; Marra, G.; Klein, N.; Radice, R.; Lado-Baleato, O.; González-Quintela, A.; Gude, F.
2019. Statistics in Medicine, 38 (27), 5161–5181. doi:10.1002/sim.8358

Muster Richtlinie Nachhaltige Forschungssoftware an den Helmholtz Zentren
Bach, F.; Bertuch, O.; Busse, C.; Castell, W. zu; Celo, S.; Denker, M.; Dinkelacker, S.; Druskat, S.; Faber, C.; Finke, A.; Fritzsch, B.; Hammitzsch, M.; Haseleu, J.; Konrad, U.; Krupa, J.; u. a.
2019

Massively Parallel Large-scale Multi-model Simulation of Tumor Development including Treatments
Berghoff, M.; Rosenbauer, J.; Schug, A.
2019, November 17. 5th Computational Approaches for Cancer Workshop (CAFCW19 2019), Denver, CO, USA, 17. November 2019

The NAStJA Framework and the Design for High-performance Computing Applications
Berghoff, M.
2019, November 15. 9th Mid-Atlantic Numerical Analysis Day (2019), Philadelphia, PA, USA, 15. November 2019

AARC Blueprint Architecture 2019
Hardt, M.; Liampotis, N.; Stevanovic, U.; Salle, M.; Kanellopoulos Christos; Jensen, J.; Memon, S.; Groep, D.; Linden, M.; Paetow, S.
2019. Zenodo. doi:10.5281/zenodo.3672785

Central limit theorems for multilevel Monte Carlo methods
Hoel, H.; Krumscheid, S.
2019. Journal of Complexity, 54, Art.-Nr.: 101407. doi:10.1016/j.jco.2019.05.001

Direct coupling analysis improves the identification of beneficial amino acid mutations for the functional thermostabilization of a delicate decarboxylase
Peng, M.; Maier, M.; Esch, J.; Schug, A.; Rabe, K. S.
2019. Biological chemistry, 400 (11), 1519–1527. doi:10.1515/hsz-2019-0156

Multivariate effect priors in bivariate semiparametric recursive Gaussian models
Thaden, H.; Klein, N.; Kneib, T.
2019. Computational Statistics & Data Analysis, 137, 51–66. doi:10.1016/j.csda.2018.12.004

An adaptive quadrature-based moment closure
Kusch, J.; Frank, M.
2019. International journal of advances in engineering sciences and applied mathematics, 11 (3), 174–186. doi:10.1007/s12572-019-00252-7

Impact of Combustion Modeling on the Spectral Response of Heat Release in LES
Zhang, F.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.; Trimis, D.; Nawroth, H.; Paschereit, C. O.
2019. Combustion science and technology, 191 (9), 1520–1540. doi:10.1080/00102202.2018.1558218

The NAStJA Framework and the Design of High-performance Application
Berghoff, M.
2019, August 29. GridKa School (2019), Karlsruhe, Deutschland, 26.–30. August 2019

On the Quality of Wall Time Estimates for Resource Allocation Prediction
Soysal, M.; Berghoff, M.; Klusáček, D.; Streit, A.
2019, August 5. 15th International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems in conjunction with International Conference on Parallel Processing (ICPP) (SRMPDS 2019), Kyōto, Japan, 5. August 2019

Using On-Demand File Systems in HPC Environments
Soysal, M.; Berghoff, M.; Zirwes, T.; Vef, M.-A.; Oeste, S.; Brinkmann, A.; Nagel, W. E.; Streit, A.
2019, Juli 17. 17th International Conference on High Performance Computing & Simulation (HPCS 2019), Dublin, Irland, 15.–19. Juli 2019

Aspekte digitaler Infrastrukturen : Forschungsdaten im Sonderforschungsbereich 980 „Episteme in Bewegung“: Herausforderungen und Perspektiven
Götzelmann, G.; Hegel, P.; Krewet, M.; Söring, S.; Tonne, D.
2019. Bibliothek Forschung und Praxis, 43 (2), 324–331. doi:10.1515/bfp-2019-2055

Multiscale Modeling: Tumor Development
Rosenbauer, J.; Berghoff, M.; Schug, A.
2019, Juni 20. 3rd ISC Workshops - ISC High Performance (2019), Frankfurt am Main, Deutschland, 16.–20. Juni 2019

Towards Continuous Benchmarking – An Automated Performance Evaluation Framework for High Performance Software
Anzt, H.; Chen, Y.-C.; Cojean, T.; Dongarra, J.; Flegar, G.; Nayak, P.; Quintana-Ortí, E. S.; Tsai, Y. M.; Wang, W.
2019. Proceedings of the Platform for Advanced Scientific Computing Conference, Article no: 9, Association for Computing Machinery (ACM). doi:10.1145/3324989.3325719

Simulation and Analysis of Protein-Fluorophore Systems for Comparison with Fluorescence Spectroscopy Data. Dissertation
Reinartz, I.
2019, Juni 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000095718

Rootless Containers with Udocker
Gomes, J.; David, M.; Martins, J. P.; Pina, J.; Campos, I.; López Garcia, A.; Orviz, P.; Kozlov, V.
2019, Juni. ISC High Performance (2019), Frankfurt am Main, Deutschland, 16.–20. Juni 2019

DEEP: Hybrid Approach for Deep Learning
Alic, A. S.; Antonacci, M.; Caballer, M.; Campos, I.; Costantini, A.; David, M.; Dlugolinsky, S.; Donvito, G.; Duma, C.; Gomes, J.; Hardt, M.; Heredia, I.; Hluchy, L.; Ito, K.; Kozlov, V.; u. a.
2019, Juni. ISC High Performance (2019), Frankfurt am Main, Deutschland, 16.–20. Juni 2019

Wie gelingt digitalisierte Forschung? Neues Open Source ELN für die Wissenschaft
Jung, N.; Tremouilhac, P.; Bach, F.; Kramer, C.; Bräse, S.; Ottleben, I.
2019. Labor-Praxis

Quantifying uncertainties in contact mechanics of rough surfaces using the multilevel Monte Carlo method
Rey, V.; Krumscheid, S.; Nobile, F.
2019. International Journal of Engineering Science, 138, 50–64. doi:10.1016/j.ijengsci.2019.02.003

Numerical prediction of air-assisted primary atomization using Smoothed Particle Hydrodynamics
Braun, S.; Wieth, L.; Holz, S.; Dauch, T. F.; Keller, M. C.; Chaussonnet, G.; Gepperth, S.; Koch, R.; Bauer, H.-J.
2019. International journal of multiphase flow, 114, 303–315. doi:10.1016/j.ijmultiphaseflow.2019.03.008

On charge percolation in slurry electrodes used in vanadium redox flow batteries
Lohaus, J.; Rall, D.; Kruse, M.; Steinberger, V.; Wessling, M.
2019. Electrochemistry Communications, 101, 104–108. doi:10.1016/j.elecom.2019.02.013

Rejoinder on: Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions
Kneib, T.; Klein, N.; Lang, S.; Umlauf, N.
2019. TEST, 28 (1), 55–59. doi:10.1007/s11749-019-00636-8

Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions
Kneib, T.; Klein, N.; Lang, S.; Umlauf, N.
2019. TEST, 28 (1), 1–39. doi:10.1007/s11749-019-00631-z

Adaptive precision in block-Jacobi preconditioning for iterative sparse linear system solvers
Anzt, H.; Dongarra, J.; Flegar, G.; Higham, N. J.; Quintana-Ortí, E. S.
2019. Concurrency and computation, 31 (6), e4460. doi:10.1002/cpe.4460

Large Scale Simulations of Cell Resolved Tissue by a Cellular Potts Model
Rosenbauer, J.; Berghoff, M.; Schug, A.
2019, März. 63rd Annual Meeting of the Biophysical Society (BPS 2019), Baltimore, MD, USA, 2.–6. März 2019

Mixed binary‐continuous copula regression models with application to adverse birth outcomes
Klein, N.; Kneib, T.; Marra, G.; Radice, R.; Rokicki, S.; McGovern, M. E.
2019. Statistics in Medicine, 38 (3), 413–436. doi:10.1002/sim.7985

Gaussian Process Responses in Distributional Regression
Riebl, H.; Klein, N.; Kneib, T.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Ed.: L.M. Machado. Vol. 2, 341–345, Statistical Modelling Society

Non-Stationary Spatial Regression for Modelling Monthly Precipitation in Germany
Marques, I.; Klein, N.; Kneib, T.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Vol 2. Ed.: L. Meira-Machado, 195–199

Modular Regression – A Lego System for Building Structured Additive Distributional Regression Models with Tensor Product Interactions
Kneib, T.; Klein, N.; Umlauf, N.; Lang, S.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Vol 1. Ed.: L. Meira-Machado, 214–219

Neural Network Regression with an Application to Leukaemia Survival Data – An Unstructured Distributional Approach
Klein, N.; Umlauf, N.; Simon, T.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Vol 1. Ed.: L. Meira-Machado, 157–160

Density regression via penalised splines dependent Dirichlet process mixture of normal models
Carvalho, V. de; Rodríguez-Álvarez, M.; Klein, N.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Vol 1. Ed.: L. Meira-Machado, 184–188

MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging–design, implementation and application on the example of DCE-MRI
Debus, C.; Floca, R.; Ingrisch, M.; Kompan, I.; Maier-Hein, K.; Abdollahi, A.; Nolden, M.
2019. BMC bioinformatics, 20 (1), Artkl.Nr.: 31. doi:10.1186/s12859-018-2588-1

An der Schnittstelle von Fach-und Informationswissenschaft : Das INF-Projekt des SFB 980 "Episteme in Bewegung : Wissenstransfers von der Alten Welt bis in die frühe Neuzeit”
Söring, S.; Götzelmann, G.; Hegel, P.; Krewet, M.; Tonne, D.
2019. Bausteine Forschungsdatenmanagement, (2, SH), 89–95. doi:10.17192/bfdm.2019.2.8083

Aristoteles auf Reisen : Handschriftenforschung in der digitalen Infrastruktur des SFB 980 „Episteme in Bewegung“
Krewet, M.; Hegel, P.; Götzelmann, G.; Tonne, D.; Söring, S.
2019. Forschungsinfrastrukturen in den digitalen Geisteswissenschaften : Wie verändern digitale Infrastrukturen die Praxis der Geisteswissenschaften? Hrsg.: M. Huber, 77–87, DFG

OCR-D: An end-to-end open source OCR framework for historical printed documents
Neudecker, C.; Baierer, K.; Federbusch, M.; Boenig, M.; Würzner, K.-M.; Hartmann, V.; Herrmann, E.
2019. EuropeanaTech Insight, 13

German-Russian astroparticle data life cycle initiative
Haungs, A.; Bychkov, I.; Dubenskaya, J.; Fedorov, O.; Heiss, A.; Kang, D.; Kazarina, Y.; Korosteleva, E.; Kostunin, D.; Kryukov, A.; Mikhailov, A.; Nguyen, M.-D.; Polgart, F.; Polyakov, S.; Postnikov, E.; u. a.
2019. 36th International Cosmic Ray Conference (ICRC 2019), Madison, WI, USA, 24.07.2019 – 01.08.2019. doi:10.22323/1.358.0284

Adoption of ARC-CE and HTCondor at GridKa Tier 1
Fischer, M.; Kuehn, E.; Schnepf, M.; Petzold, A.; Heiss, A.
2019. The European physical journal / Web of Conferences, 214, Art.-Nr.: 03053. doi:10.1051/epjconf/201921403053

Einblicke in die Klimaforschung – Perspektiven eines computergestützten mathematischen Projekttages für Oberstufenschüler/innen
Hattebuhr, M.; Frank, M.
2019. ISTRON-Tagung (2019), Berlin, Deutschland, 28. September 2019

Computergestützte mathematische Workshops für Oberstufenschüler/innen zum Thema Klimawandel
Hattebuhr, M.; Frank, M.
2019. IPCC Jahrestagung (2019), Nauen, Deutschland, 20.–21. März 2019

Complex modeling: Does climate change really exist? – Perspectives of a project day with high school students
Hattebuhr, M.; Frank, M.
2019. 11th Congress of the European Society for Researchin Mathematics Education

Parallel selection on GPUs
Ribizel, T.; Anzt, H.
2019. Parallel computing, 91, Article: 102588. doi:10.1016/j.parco.2019.102588

A Positive Asymptotic-Preserving Scheme for Linear Kinetic Transport Equations
Laiu, M. P.; Frank, M.; Hauck, C. D.
2019. SIAM journal on scientific computing, 41 (3), A1500–A1526. doi:10.1137/18M1196297

Dynamic Integration and Management of Opportunistic Resources for HEP
Schnepf, M. J.; Cube, R. F. von; Fischer, M.; Giffels, M.; Heidecker, C.; Heiss, A.; Kuehn, E.; Petzold, A.; Quast, G.; Sauter, M.
2019. The European physical journal / Web of Conferences, 214, 08009. doi:10.1051/epjconf/201921408009

Advancing throughput of HEP analysis work-flows using caching concepts
Caspart, R.; Fischer, M.; Giffels, M.; Heidecker, C.; Kühn, E.; Quast, G.; Sauter, M.; Schnepf, M. J.; Cube, R. F. von
2019. The European physical journal / Web of Conferences, 214, Article no: 04007. doi:10.1051/epjconf/201921404007

Massively Parallel Large-scale Multi-model Simulation of Tumor Development
Berghoff, M.; Rosenbauer, J.; Schug, A.
2019. The International Conference for High Performance Computing, Networking, Storage, and Analysis (2019), Denver, CO, USA, 17.–22. November 2019

Book of Abstracts: Sixth bwHPC Symposium, 30 September 2019, Karlsruhe, Germany
Denev, J.; Barthel, R.; Frank, M. (Hrsg.)
2019. Karlsruher Institut für Technologie (KIT)

A low-rank method for time-dependent transport calculations
Peng, Z.; McClarren, R. G.; Frank, M.
2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C), Portland, OR, August 25-29, 2019, 957–966, American Nuclear Society (ANS)

Ray-effect mitigation for the discrete ordinates method using artificial scattering
Camminady, T.; Frank, M.; Hauck, C. D.; Kusch, J.
2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C), Portland, OR, August 25-29, 2019, 459–466, American Nuclear Society (ANS)

Highly uniform quadrature sets for the discrete ordinates method
Camminady, T.; Frank, M.; Kusch, J.
2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C), Portland, OR, August 25-29, 2019, 449–458, American Nuclear Society (ANS)

Intrusive uncertainty quantification for applications in fluid dynamics
Kusch, J.; Wolters, J.; Frank, M.
2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C), Portland, OR, August 25-29, 2019, 1918–1927, American Nuclear Society (ANS)

Benchmarking Deep Learning Infrastructures by Means of TensorFlow and Containers
Grupp, A.; Kozlov, V.; Campos, I.; David, M.; Gomes, J.; López García, Á.
2019. High Performance Computing : ISC High Performance 2019 International Workshops, Frankfurt, Germany, June 16-20, 2019. Ed.: M. Weiland, 478–489, Springer International Publishing. doi:10.1007/978-3-030-34356-9_36

Towards Seamless Simulations of Polar Stratospheric Clouds and Ozone in the Polar Stratosphere with ICON-ART. Dissertation
Weimer, M.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000100338

ParILUT - A parallel threshold ILU for GPUS
Anzt, H.; Ribizel, T.; Flegar, G.; Chow, E.; Dongarra, J.
2019. Proceedings 2019 IEEE 33rd International Parallel and Distributed Processing Symposium, IPDPS 2019: 20-24 May 2019, Rio de Janeiro, Brazil, 231–241, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPS.2019.00033

Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000-2016 period
Zhao, Y.; Saunois, M.; Bousquet, P.; Lin, X.; Berchet, A.; Hegglin, M. I.; Canadell, J. G.; Jackson, R. B.; Hauglustaine, D. A.; Szopa, S.; Stavert, A. R.; Abraham, N. L.; Archibald, A. T.; Bekki, S.; Deushi, M.; u. a.
2019. Atmospheric chemistry and physics, 19 (21), 13701–13723. doi:10.5194/acp-19-13701-2019

PAPI software-defined events for in-depth performance analysis
Jagode, H.; Danalis, A.; Anzt, H.; Dongarra, J.
2019. The international journal of high performance computing applications, 33 (6), 1113–1127. doi:10.1177/1094342019846287

Data Encoding in Lossless Prediction-Based Compression Algorithms
Cayoglu, U.; Tristram, F.; Meyer, J.; Schröter, J.; Kerzenmacher, T.; Braesicke, P.; Streit, A.
2019. IEEE 15th International Conference on eScience : 24-27 September 2019, San Diego, California : proceedings. Ed.: Ilkay Altintas, 226–234, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eScience.2019.00032

On Advancement of Information Spaces to Improve Prediction-Based Compression
Cayoglu, U.; Tristram, F.; Meyer, J.; Kerzenmacher, T.; Braesicke, P.; Streit, A.
2019. INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft Hrsg.: K. David, 271–272, Gesellschaft für Informatik (GI). doi:10.18420/inf2019_39

Enlargement of Submicron Gas‐Borne Particles by Heterogeneous Condensation for Energy‐Efficient Aerosol Separation
Hamberger, P.; Koch, D. P.; Sinanis, S.; Schaber, K.
2019. Chemical engineering & technology, 42 (11), 2458–2464. doi:10.1002/ceat.201800720

Application of Mixtures of Gaussians for Tracking Clusters in Spatio-temporal Data
Ertl, B.; Meyer, J.; Streit, A.; Schneider, M.
2019. Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, September 17-19, 2019, in Vienna, Austria, Vol. 1. Ed.: A. Fred, 45–54, SciTePress. doi:10.5220/0007949700450054

Algorithm Selection in Auction-based Allocation of Cloud Computing Resources. Dissertation
Gudu, D.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000098816

Portfolio optimization and model predictive control: A kinetic approach
Trimborn, T.; Pareschi, L.; Frank, M.
2019. Discrete and continuous dynamical systems / B, 24 (11), 6209–6238. doi:10.3934/dcdsb.2019136

Numerical and Experimental Investigations of Primary Breakup of High-Viscous Fluid at Elevated Pressure [in press]
Zhang, F.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Dimosthenis, T.; Kolb, T.
2019. 29th European Conference on Liquid Atomization and Spray Systems, Paris, 2-4 Sep 2019

Federated Identity Management for Research
WISE SCI Working Group; Barton, T.; Gietz, P.; Kelsey, D.; Koranda, S.; Short, H.; Stevanovic, U.
2019. (A. Forti, L. Betev, M. Litmaath, O. Smirnova & P. Hristov, Hrsg.) The European physical journal / Web of Conferences, 214, Art.Nr.: 03044. doi:10.1051/epjconf/201921403044

The effect of atmospheric nudging on the stratospheric residual circulation in chemistry–climate models
Chrysanthou, A.; Maycock, A. C.; Chipperfield, M. P.; Dhomse, S.; Garny, H.; Kinnison, D.; Akiyoshi, H.; Deushi, M.; Garcia, R. R.; Jöckel, P.; Kirner, O.; Pitari, G.; Plummer, D. A.; Revell, L.; Rozanov, E.; u. a.
2019. Atmospheric chemistry and physics, 19 (17), 11559–11586. doi:10.5194/acp-19-11559-2019

Next Generation of HEP CPU Benchmarks
Giordano, D.; Alef, M.; Michelotto, M.
2019. The European physical journal / Web of Conferences, 214, Article no: 08011. doi:10.1051/epjconf/201921408011

Optimization of robust aiming strategies in solar tower power plants
Richter, P.; Kepp, F.; Büsing, C.; Kuhnke, S.
2019. SolarPACES 2018. Ed.: C. Richter, 030045, American Institute of Physics (AIP). doi:10.1063/1.5117557

Are we doing the right thing? - A critical analysis of the academic HPC community
Anzt, H.; Flegar, G.
2019. 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 739–745, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPSW.2019.00122

Approximate and exact selection on GPUs
Ribizel, T.; Anzt, H.
2019. 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 471–478, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPSW.2019.00088

Clear-sky ultraviolet radiation modelling using output from the Chemistry Climate Model Initiative
Lamy, K.; Portafaix, T.; Josse, B.; Brogniez, C.; Godin-Beekmann, S.; Bencherif, H.; Revell, L.; Akiyoshi, H.; Bekki, S.; Hegglin, M. I.; Jöckel, P.; Kirner, O.; Liley, B.; Marecal, V.; Morgenstern, O.; u. a.
2019. Atmospheric chemistry and physics, 19 (15), 10087–10110. doi:10.5194/acp-19-10087-2019

Unsteady pure straining effects on lean premixed flames of different Lewis numbers
Denev, J. A.; Naydenova, I.; Zhang, F.; Zirwes, T.; Bockhorn, H.
2019. 9th European Combustion Meeting (ECM), Lissabon, Portugal, 14 - 17 April 2019

2D and 3D numerical simulation of chemiluminescent radical concentrations during side-wall quenching of premixed methane and propane flames [in press]
Zirwes, T.; Häber, T.; Zhang, F.; Kosaka, H.; Bockhorn, H.; Suntz, R.; Dreizler, A.; Janicka, J.
2019. 9th European Combustion Meeting (ECM), Lissabon, Portugal, 14 - 17 April 2019

Neues Konzept zur skalierbaren, explorativen Analyse großer Zeitreihendaten mit Anwendung auf umfangreiche Stromnetz-Messdaten. Dissertation
Bach, F.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000097843

Numerical simulation of sulfur combustors with high-power-density [in press]
Zhang, F.; Heidarifatasmi, H.; Zirwes, T.; Fedoryk, M.; Harth, S.; Sebbar, N.; Habisreuther, P.; Trimis, D.; Bockhorn, H.
2019. 9th European Combustion Meeting (ECM), Lissabon, Portugal, 14 - 17 April 2019

Numerical Simulation of Turbulent Flame Propagation in a Fan-Stirred Combustion Bomb at Elevated Pressures [in press]
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.; Trimis, D.
2019. 27th International Colloquium on the Dynamics of Explosions and Reactive Systems, Beijing, China, 8th July - 2nd August 2019

Properties of Z±c(3900) produced in p¯p collisions
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2019. Physical review / D, 100 (1), 012005. doi:10.1103/PhysRevD.100.012005

Clustering as Approximation Method to Optimize Hydrological Simulations
Azmi, E.; Ehret, U.; Meyer, J.; Pruijssen, R. van; Streit, A.; Strobl, M.
2019. Euro-Par 2019: Parallel Processing – 25th International Conference on Parallel and Distributed Computing, Göttingen, Germany, August 26–30, 2019, Proceedings. Ed.: R. Yahyapour. Ed.: R. Yahyapour, 256–269, Springer International Publishing. doi:10.1007/978-3-030-29400-7_19

Large-Scale Quasi-DNS of Mixed-Mode Turbulent Combustion [in press]
Zirwes, T.; Zhang, F.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2019. 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Vienna, Austria, February 18-22, 1019. Ed.: J. Eberhardsteiner, TU Verlag

Ignition behaviour of sulfur in air based on modified reaction kinetics [in press]
Zirwes, T.; Sebbar, N.; Habisreuther, P.; Harth, S.; Zhang, F.; Bockhorn, H.; Trimis, D.
2019. 11th Mediterranean Combustion Symposium (MCS11), Tenerife, Spain, 16-20 June 2019

Research Data Repository Interoperability WG Final Recommendations
Jejkal, T.; Wilcox, D.
2019. Research Data Alliance (RDA). doi:10.15497/RDA00025

Identification of evolutionary and kinetic drivers of NAD-dependent signaling
Bockwoldt, M.; Houry, D.; Niere, M.; Gossmann, T. I.; Reinartz, I.; Schug, A.; Ziegler, M.; Heiland, I.
2019. Proceedings of the National Academy of Sciences of the United States of America, 116 (32), 15957–15966. doi:10.1073/pnas.1902346116

Close Nozzle Spray Characteristics of a Prefilming Airblast Atomizer
Holz, S.; Braun, S.; Chaussonnet, G.; Koch, R.; Bauer, H.-J.
2019. Energies, 12 (14), 2835. doi:10.3390/en12142835

Large-Scale Quasi-DNS of Mixed-Mode Turbulent Combustion
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2019. 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM 2019), Wien, Österreich, 18.–22. Februar 2019

2D and 3D numerical simulation of chemiluminescent radical concentrations during side-wall quenching of premixed methane and propane flames
Zirwes, T.; Häber, T.; Zhang, F.; Kosaka, H.; Bockhorn, H.; Suntz, R.; Dreizler, A.; Janicka, J.
2019. 9th European Combustion Meeting (ECM 2019), Lissabon, Portugal, 14.–17. April 2019

Numerical simulation of sulfur combustors with high-power-density
Zhang, F.; Heidarifatasmi, H.; Zirwes, T.; Fedoryk, M.; Harth, S.; Sebbar, N.; Habisreuther, P.; Trimis, D.; Bockhorn, H.
2019. 9th European Combustion Meeting (ECM 2019), Lissabon, Portugal, 14.–17. April 2019

Unsteady pure straining effects on lean premixed flames of different Lewis numbers
Denev, J. A.; Naydenova, I.; Zhang, F.; Zirwes, T.; Bockhorn, H.
2019. 9th European Combustion Meeting (ECM 2019), Lissabon, Portugal, 14.–17. April 2019

Entwicklung von Schwefelbrennern mit hohen Leistungsdichten
Fedoryk, M.; Zhang, F.; Heidarifatasmi, H.; Zirwes, T.; Sebbar, N.; Harth, S.; Trimis, D.
2019. Jahrestreffen der ProcessNet-Fachgruppe "Hochtemperaturtechnik" (2019), Karlsruhe, Deutschland, 2.–3. April 2019

LES of Combustion Noise from a Turbulent Premixed Jet Flame
Zhang, F.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2019. 17th International Conference on Numerical Combustion (2019), Aachen, Deutschland, 6.–8. Mai 2019

Spectral response of heat release in LES combustion modeling
Zhang, F.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2019. 17th International Conference on Numerical Combustion (2019), Aachen, Deutschland, 6.–8. Mai 2019

Implementation of Flame Particle Tracking for Studying Laminar and Turbulent Flame Dynamics
Zirwes, T.; Zhang, F.; Habisreuther, P.; Denev, J. A.; Bockhorn, H.; Trimis, D.
2019. 17th International Conference on Numerical Combustion (2019), Aachen, Deutschland, 6.–8. Mai 2019

Numerical Simulation of Turbulent Flame Propagation in a Fan-Stirred Combustion Bomb at Elevated Pressures
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.; Trimis, D.
2019. 27th International Colloquium on the Dynamics of Explosions and Reactive Systems (ICDERS 2019), Peking, China, 28. Juli–2. August 2019

Numerical and Experimental Investigations of Primary Breakup of High-Viscous Fluid at Elevated Pressure
Zhang, F.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Trimis, D.; Kolb, T.
2019. 29th European Conference Liquid Atomization & Spray Systems (ILASS 2019), Paris, Frankreich, 2.–4. September 2019

Numerische Untersuchung eines Schwefelverbrennungssystem
Zhang, F.; Heidarifatasmi, H.; Harth, S.; Zirwes, T.; Sebbar, N.; Fedoryk, M.; Trimis, D.
2019. 29. Deutscher Flammentag (2019), Bochum, Deutschland, 17.–18. September 2019

Effect of elevated pressure on primary jet-breakup: Basic research for entrained flow gasification
Zhang, F.; Müller, T.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Trimis, D.; Kolb, T.
2019. 29. Deutscher Flammentag (2019), Bochum, Deutschland, 17.–18. September 2019

Identification of Flame Regimes in Partially Premixed Combustion from a Quasi-DNS Dataset [in press]
Zirwes, T.; Zhang, F.; Hansinger, M.; Bockhorn, H.; Pfitzner, M.; Trimis, D.
2019. International Workshop on Clean Combustion: Principles and Applications (2019), Darmstadt, Deutschland, 25.–26. September 2019

Improved Vectorization for Efficient Chemistry Computations in OpenFOAM for Large Scale Combustion Simulations
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2019. High Performance Computing in Science and Engineering ’18 - Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2018. Ed.: W. E. Nagel, 209–224, Springer International Publishing

SABCEMM: A Simulator for Agent-Based Computational Economic Market Models
Trimborn, T.; Otte, P.; Cramer, S.; Beikirch, M.; Pabich, E.; Frank, M.
2019. Computational economics. doi:10.1007/s10614-019-09910-1

On the Quality of Wall Time Estimates for Resource Allocation Prediction
Soysal, M.; Berghoff, M.; Klusáček, D.; Streit, A.
2019. ICPP 2019 Proceedings of the 48th International Conference on Parallel Processing: Workshops, Kyoto, Japan — August 05 - 08, 2019, Artikel Nr.: 23 /1–8, Association for Computing Machinery (ACM). doi:10.1145/3339186.3339204

Change in Flame Geometry of an Ethanol Spray Flame by Varying the Spray Characteristics
Galeazzo, F. C. C.; Fukumasu, N. K.; Denev, J. A.; Weis, C.; Habisreuther, P.; Krieger Filho, G. C.
2019. Combustion science and technology, 191 (9), 1693–1710. doi:10.1080/00102202.2019.1639682

Unusual chlorine partitioning in the 2015/16 Arctic winter lowermost stratosphere: Observations and simulations
Johansson, S.; Santee, M. L.; Grooß, J.-U.; Höpfner, M.; Braun, M.; Friedl-Vallon, F.; Khosrawi, F.; Kirner, O.; Kretschmer, E.; Oelhaf, H.; Orphal, J.; Sinnhuber, B.-M.; Tritscher, I.; Ungermann, J.; Walker, K. A.; u. a.
2019. Atmospheric chemistry and physics, 19 (12), 8311–8338. doi:10.5194/acp-19-8311-2019

Theorien von Autorschaft und Stil in Bewegung: Stilistik und Stilometrie in der Romania
Rißler-Pipka, N. (Hrsg.)
2019. Akademische Verlagsgemeinschaft

Einleitung
Rißler-Pipka, N.
2019. Romanische Studien - Beihefte, 6, 5–19

In Search of a New Language: Measuring Style of Góngora and Picasso
Rißler-Pipka, N.
2019. Romanische Studien - Beihefte, 6, 117–149

Tools for Analyzing Parallel I/O
Kunkel, J. M.; Betke, E.; Bryson, M.; Carns, P.; Francis, R.; Frings, W.; Laifer, R.; Mendez, S.
2019. International Conference on High Performance Computing, ISC High Performance 2018; Frankfurt; Germany; 28 June 2018 through 28 June 2018. Ed.: M. Weiland, 49–70, Springer. doi:10.1007/978-3-030-02465-9_4

Rising Up: Hierarchical Metal–Organic Frameworks in Experiments and Simulations
Luo, Y.; Ahmad, M.; Schug, A.; Tsotsalas, M.
2019. Advanced materials, 31 (26), Art.-Nr.: 1901744. doi:10.1002/adma.201901744

Theorien von Autorschaft und Stil in Bewegung : Stilistik und Stilometrie in der Romania [in press]
Rißler-Pipka, N. (Hrsg.)
2019. Akademische Verlagsgemeinschaft

Using On-demand File Systems in HPC Environments
Soysal, M.; Berghoff, M.; Zirwes, T.; Vef, M.-A.; Oeste, S.; Brinkman, A.; Nagel, W. E.; Streit, A.
2019. The 17th Annual Meeting of the 2019 International Conference on High Performance Computing & Simulation (HPCS 2019), Dublin, IR, July 15-19, 2019. doi:10.1109/HPCS48598.2019.9188216

Toward a modular precision ecosystem for high-performance computing
Anzt, H.; Flegar, G.; Grützmacher, T.; Quintana-Ortí, E. S.
2019. The international journal of high performance computing applications, 33 (6), 1069–1078. doi:10.1177/1094342019846547

Labelling OCR Ground Truth for Usage in Repositories
Boenig, M.; Baierer, K.; Hartmann, V.; Federbusch, M.; Neudecker, C.
2019. Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage (DATeCH2019), 3–8, Association for Computing Machinery (ACM). doi:10.1145/3322905.3322916

OCR-D: An end-to-end open source OCR framework for historical printed documents
Neudecker, C.; Baierer, K.; Federbusch, M.; Boenig, M.; Würzner, K.-M.; Hartmann, V.; Herrmann, E.
2019. Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage (DATeCH2019), 53–58, Association for Computing Machinery (ACM). doi:10.1145/3322905.3322917

Machine learning-aided numerical linear Algebra: Convolutional neural networks for the efficient preconditioner generation
Götz, M.; Anzt, H.
2019. Proceedings of ScalA 2018: 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 49–56, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalA.2018.00010

High-Performance GPU Implementation of PageRank with Reduced Precision Based on Mantissa Segmentation
Grützmacher, T.; Anzt, H.; Scheidegger, F.; Quintana-Orti, E. S.
2019. Proceedings of IA³ 2018: 8th Workshop on Irregular Applications: Architectures and Algorithms, 61–68, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IA3.2018.00015

Variable-Size Batched Condition Number Calculation on GPUs
Anzt, H.; Dongarra, J.; Flegar, G.; Grützmacher, T.
2019. 2018 30th International Symposium on Computer Architecture and High Performance Computing: SBAC-PAD 2018 ; Lyon, France, 24-27 September 2018 ; Proceedings, 132–139, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CAHPC.2018.8645907

A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs
Anzt, H.; Dongarra, J.
2019. 2018 30th International Symposium on Computer Architecture and High Performance Computing: SBAC-PAD 2018 ; Lyon, France, 24-27 September 2018 ; Proceedings, 229–232, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CAHPC.2018.8645946

Ein Web Annotation Protocol Server zur Untersuchung vormoderner Wissensbestände
Tonne, D.; Götzelmann, G.; Hegel, P.; Krewet, M.; Hübner, J.; Söring, S.; Löffler, A.; Hitzker, M.; Höfler, M.; Schmidt, T.
2019. DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts. Hrsg.: Patrick Sahle, 283–285, Zenodo

Zeitungen und Zeitschriften als multimodale, digitale Forschungsobjekte: Theorien und Methoden
Rißler-Pipka, N.; Neudecker, C.; Resch, C.; Kampkaspar, D.; Lehmann, J.; Herzgsell, T.
2019. DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts. Hrsg.: P. Sahle, 77–81

L’esthétique numérique de Picasso
Rißler-Pipka, N.
2019. Philologie im Netz, 2019 (16), 39–59

Zwischen Genres und Medien: Formen moderner Prosa in Frankreich = Entre genres et médias: formes de la prose moderne en France
Rißler-Pipka, N.; Schöch, C. (Hrsg.)
2019. Freie Universität Berlin

Rapid interpretation of small-angle X-ray scattering data
Weiel, M.; Reinartz, I.; Schug, A.
2019. PLoS Computational Biology, 15 (3), e1006900. doi:10.1371/journal.pcbi.1006900

Wie sich die Bilder gleichen. Bildähnlichkeitssuche in Drucken des 16. Jahrhunderts
Götzelmann, G.
2019. DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts. Hrsg.: Patrick Sahle, 358–359, Zenodo

Extreme Data Workshop 2018 Forschungszentrum Jülich, 18 – 19 September 2018 Proceedings
Schultz, M.; Pleiter, D.; Bauer, P. (Hrsg.)
2019. Forschungszentrum Jülich

AARC Blueprint Architecture 2018: A first look at the community-first approach
Hardt, M.; Stevanovic, U.
2019

Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems
Cavallaro, G.; Kozlov, V.; Götz, M.; Riedel, M.
2019. Proceedings of 2019 Big Data from Space (BiDS’19). Ed.: S. Pierre, 177–180. doi:10.2760/848593

Implementers Guide to the WISE Baseline Acceptable Use Policy
WISE SCI Working Group; Groep, D.; Neilson, I.; Hardt, M.; Stevanovic, U.
2019. doi:10.5445/IR/1000093121

Maximum-principle-satisfying second-order Intrusive Polynomial Moment scheme
Kusch, J.; Alldredge, G. W.; Frank, M.
2019. SMAI Journal of Computational Mathematics, 5, 23–51. doi:10.5802/smai-jcm.42

Procedures for systematic capture and management of analytical data in academia
Potthoff, J.; Tremouilhac, P.; Hodapp, P.; Neumair, B.; Bräse, S.; Jung, N.
2019. Analytica Chimica Acta: X, 1, Article: 100007. doi:10.1016/j.acax.2019.100007

Potential Arctic cirrus cloud feedbacks on the composition of te UTLS
Haenel, F.; Woiwode, W.; Höpfner, M.; Ruhnke, R.; Khosrawi, F.; Kirner, O.; Friedl-Vallon, F.; Johansson, S.; Kleinert, A.; Schröter, J.; Sinnhuber, B.-M.
2019. DPG-Frühjahrstagung der Sektion Materie und Kosmos (SMuK), Fachverband Umweltphysik (2019), München, Deutschland, 17.–22. März 2019

Ray effect mitigation for the discrete ordinates method through quadrature rotation
Camminady, T.; Frank, M.; Küpper, K.; Kusch, J.
2019. Journal of computational physics, 382, 105–123. doi:10.1016/j.jcp.2019.01.016

On Using Clustering for the Optimization of Hydrological Simulations
Azmi, E.
2019. IEEE International Conference on Data Mining Workshops(ICDMW), Singapore, November 17 - 20 2018, 1495–1496, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICDMW.2018.00215

A unified comparative study of heuristic algorithms for double combinatorial auctions: Locality-constrained resource allocation problems
Gudu, D.; Hardt, M.; Streit, A.
2019. Agents and Artificial Intelligence: 10th International Conference, ICAART 2018, Funchal, Madeira, Portugal, January 16-18,2018. Revised Selected Papers., 3–22. doi:10.1007/978-3-030-05453-3_1

Automatic Layout Analysis and Visual Exploration of Multidimensional Datasets with Applications in the Digital Humanities. Dissertation
Chandna, S.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000089239

The GridKa Tape System: status and outlook
Ressmann, D.; Lobontu, D.; Beitzinger, M.; Schäfer, K.; Heiss, A.; Petzold, A.; Musheghyan, H.
2019. The European physical journal / Web of Conferences, 214, Art. Nr.: 04029. doi:10.1051/epjconf/201921404029

Concept and Analysis of Information Spaces to improve Prediction-Based Compression
Cayoglu, U.; Tristram, F.; Meyer, J.; Kerzenmacher, T.; Braesicke, P.; Streit, A.
2019. 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, December 10 - 13, 2018. Ed.: Y. Song, 3392–3401, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData.2018.8622313

Ignition of combustible mixtures by hot particles at varying relative speeds
Zirwes, T.; Zhang, F.; Häber, T.; Bockhorn, H.
2019. Combustion science and technology, 191 (1), 178–195. doi:10.1080/00102202.2018.1435530

Specification for expressing resource capabilities (AARC-G027)
Hardt, M. (Hrsg.)
2018. GÉANT. doi:10.5281/zenodo.2247446

Studying the occurrence and burnt area of wildfires using zero-one-inflated structured additive beta regression
Ríos-Pena, L.; Kneib, T.; Cadarso-Suárez, C.; Klein, N.; Marey-Pérez, M.
2018. Environmental Modelling & Software, 110, 107–118. doi:10.1016/j.envsoft.2018.03.008

Feasibility and robustness of dynamic 18F-FET PET based tracer kinetic models applied to patients with recurrent high-grade glioma prior to carbon ion irradiation
Debus, C.; Afshar-Oromieh, A.; Floca, R.; Ingrisch, M.; Knoll, M.; Debus, J.; Haberkorn, U.; Abdollahi, A.
2018. Scientific Reports, 8 (1), Artkl.Nr.: 14760. doi:10.1038/s41598-018-33034-5

Impact of 18F-FET PET on Target Volume Definition and Tumor Progression of Recurrent High Grade Glioma Treated with Carbon-Ion Radiotherapy
Debus, C.; Waltenberger, M.; Floca, R.; Afshar-Oromieh, A.; Bougatf, N.; Adeberg, S.; Heiland, S.; Bendszus, M.; Wick, W.; Rieken, S.; Haberkorn, U.; Debus, J.; Knoll, M.; Abdollahi, A.
2018. Scientific Reports, 8 (1), Artkl.Nr.: 7201. doi:10.1038/s41598-018-25350-7

On approximative linear Boltzmann transport equation for charged particles
Tervo, J.; Kokkonen, P.; Frank, M.; Herty, M.
2018. Mathematical models and methods in applied sciences (M 3 AS), 28 (14), 2905–2939. doi:10.1142/S0218202518500641

Stratospheric ozone loss over the Eurasian continent induced by the polar vortex shift
Zhang, J.; Tian, W.; Xie, F.; Chipperfield, M. P.; Feng, W.; Son, S.-W.; Abraham, N. L.; Archibald, A. T.; Bekki, S.; Butchart, N.; Deushi, M.; Dhomse, S.; Han, Y.; Jöckel, P.; Kinnison, D.; u. a.
2018. Nature Communications, 9 (1), 206. doi:10.1038/s41467-017-02565-2

Guidelines for Secure Operation of Attribute Authorities and other issuers of access-granting statements
Groep, D. L.; Kelsey, D.; Short, H.; Sallé, M.; Stevanovic, U.; Paetow, S.; Kremers, M.
2018. Zenodo. doi:10.5281/zenodo.3234926

Non-Collective Scalable Global Network Based on Local Communications
Berghoff, M.; Kondov, I.
2018, November 12. 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA 2018), Dallas, TX, USA, 11.–16. November 2018

The NAStJA Framework: Non-Collective Scalable Global Communications
Berghoff, M.; Kondov, I.
2018, November. International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2018), Dallas, TX, USA, 11.–16. November 2018

A comparative study of limiting strategies in discontinuous Galerkin schemes for the model of radiation transport
Chidyagwai, P.; Frank, M.; Schneider, F.; Seibold, B.
2018. Journal of computational and applied mathematics, 342, 399–418. doi:10.1016/j.cam.2018.04.017

More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach
Helbich, M.; Klein, N.; Roberts, H.; Hagedoorn, P.; Groenewegen, P. P.
2018. Environmental Research, 166, 290–297. doi:10.1016/j.envres.2018.06.010

Quantifying river incision into low-relief surfaces using local and catchment-wide 10Be denudation rates
Wolff, R.; Hetzel, R.; Strobl, M.
2018. Earth surface processes and landforms, 43 (11), 2327–2341. doi:10.1002/esp.4394

The NAStJA Framework - Efficient and Flexible
Berghoff, M.; Kondov, I.
2018, September. International Symposium on Computational Science at Scale (CoSaS 2018), Erlangen, Deutschland, 5.–7. September 2018

Formation of a Secretion-Competent Protein Complex by a Dynamic Wrap-around Binding Mechanism
Gupta, A. A.; Reinartz, I.; Karunanithy, G.; Spilotros, A.; Jonna, V. R.; Hofer, A.; Svergun, D. I.; Baldwin, A. J.; Schug, A.; Wolf-Watz, M.
2018. Journal of molecular biology, 430 (18), 3157–3169. doi:10.1016/j.jmb.2018.07.014

Bayesian Multivariate Distributional Regression With Skewed Responses and Skewed Random Effects
Michaelis, P.; Klein, N.; Kneib, T.
2018. Journal of Computational and Graphical Statistics, 27 (3), 602–611. doi:10.1080/10618600.2017.1395343

Perturbation-based inference for diffusion processes: Obtaining effective models from multiscale data
Krumscheid, S.
2018. Mathematical Models and Methods in Applied Sciences, 28 (08), 1565–1597. doi:10.1142/S0218202518500434

A new high-order fluid solver for tokamak edge plasma transport simulations based on a magnetic-field independent discretization
Giorgiani, G.; Camminady, T.; Bufferand, H.; Ciraolo, G.; Ghendrih, P.; Guillard, H.; Heumann, H.; Nkonga, B.; Schwander, F.; Serre, E.; Tamain, P.
2018. Contributions to plasma physics, 58 (6-8), 688–695. doi:10.1002/ctpp.201700172

Best-effort inductive logic programming via fine-grained cost-based hypothesis generation. The inspire system at the inductive logic programming competition
Schüller, P.; Benz, M.
2018. Machine learning, 107 (7), 1141–1169. doi:10.1007/s10994-018-5708-2

A simulation tool to predict spontaneous aerosol formation in gas-liquid contact devices
Hamberger, P.; Schaber, K.; Piccioni Koch, D.
2018, Juni 12. 32. Ausstellungstagung für chemisches Apparatewesen (ACHEMA 2018), Frankfurt am Main, Deutschland, 11.–15. Juni 2018

Sandboxing of biomedical applications in Linux containers based on system call evaluation
Witt, M.; Jansen, C.; Krefting, D.; Streit, A.
2018. Concurrency and computation, 30 (12), e4484. doi:10.1002/cpe.4484

Quasi-steady state reduction for the Michaelis–Menten reaction–diffusion system
Frank, M.; Lax, C.; Walcher, S.; Wittich, O.
2018. Journal of mathematical chemistry, 56 (6), 1759–1781. doi:10.1007/s10910-018-0891-8

Using Jacobi iterations and blocking for solving sparse triangular systems in incomplete factorization preconditioning
Chow, E.; Anzt, H.; Scott, J.; Dongarra, J.
2018. Journal of parallel and distributed computing, 119, 219–230. doi:10.1016/j.jpdc.2018.04.017

On existence of solutions for Boltzmann Continuous Slowing Down transport equation
Tervo, J.; Kokkonen, P.; Frank, M.; Herty, M.
2018. Journal of mathematical analysis and applications, 460 (1), 271–301. doi:10.1016/j.jmaa.2017.11.052

Crystal-melt interface mobility in bcc Fe: Linking molecular dynamics to phase-field and phase-field crystal modeling
Guerdane, M.; Berghoff, M.
2018. Physical review / B, 97 (14), 144105. doi:10.1103/PhysRevB.97.144105

Simulation of FRET dyes allows quantitative comparison against experimental data
Reinartz, I.; Sinner, C.; Nettels, D.; Stucki-Buchli, B.; Stockmar, F.; Panek, P. T.; Jacob, C. R.; Nienhaus, G. U.; Schuler, B.; Schug, A.
2018. The journal of chemical physics, 148 (12), 123321. doi:10.1063/1.5010434

Cellular Potts Models for Neural Tissue Simulations
Rosenbauer, J.; Berghoff, M.; Schug, A.
2018, März 12. DPG-Frühjahrstagung und EPS-CMD27 (2018), Berlin, Deutschland, 11.–16. März 2018

Optimization and performance evaluation of the IDR iterative Krylov solver on GPUs
Anzt, H.; Kreutzer, M.; Ponce, E.; Peterson, G. D.; Wellein, G.; Dongarra, J.
2018. The international journal of high performance computing applications, 32 (2), 220–230. doi:10.1177/1094342016646844

Intrusive methods in uncertainty quantification and their connection to kinetic theory
Kusch, J.; Frank, M.
2018. International journal of advances in engineering sciences and applied mathematics, 10 (1), 54–69. doi:10.1007/s12572-018-0211-3

A spectral Galerkin method for the fractional order diffusion and wave equation
Camminady, T.; Frank, M.
2018. International journal of advances in engineering sciences and applied mathematics, 10 (1), 90–104. doi:10.1007/s12572-018-0208-y

P-PIF: a ProvONE provenance interoperability framework for analyzing heterogeneous workflow specifications and provenance traces
Prabhune, A.; Zweig, A.; Stotzka, R.; Hesser, J.; Gertz, M.
2018. Distributed and parallel databases, 36 (1), 219–264. doi:10.1007/s10619-017-7216-y

A non-noble Cr–Ni-based catalyst for the oxygen reduction reaction in alkaline polymer electrolyte fuel cells
Faubert, P.; Kondov, I.; Qazzazie, D.; Yurchenko, O.; Müller, C.
2018. MRS communications, 8 (01), 160–167. doi:10.1557/mrc.2018.13

Weiterentwicklung eines Simulationsmodells zur Beschreibung der Aerosolbildung in Gaswäschern
Hamberger, P.; Schaber, K.; Piccioni Koch, D.
2018, Februar 20. Jahrestreffen der ProcessNet-Fachgruppe Gasreinigung und des TAK Aerosoltechnik (2018), Erlangen, Deutschland, 19.–20. Februar 2018

SSAGES : Software Suite for Advanced General Ensemble Simulations
Sidky, H.; Colón, Y. J.; Helfferich, J.; Sikora, B. J.; Bezik, C.; Chu, W.; Giberti, F.; Guo, A. Z.; Jiang, X.; Lequieu, J.; Li, J.; Moller, J.; Quevillon, M. J.; Rahimi, M.; Ramezani-Dakhel, H.; u. a.
2018. The journal of chemical physics, 148 (4), Art.Nr. 044104. doi:10.1063/1.5008853

Effect Selection in Distributional Regression
Klein, N.; Carlan, M.; Kneib, T.; Lang, S.; Wagner, H.
2018. Proceedings of the 33th International Workshop on Statistical Modelling. Vol. 1, 157–162, Statistical Modelling Society

Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany
Pross, C.; Strumann, C.; Geissler, A.; Herwartz, H.; Klein, N.
2018. (A. Arrieta, Hrsg.) PLOS ONE, 13 (9), e0203017. doi:10.1371/journal.pone.0203017

Multilevel Monte Carlo Approximation of Functions
Krumscheid, S.; Nobile, F.
2018. SIAM/ASA Journal on Uncertainty Quantification, 6 (3), 1256–1293. doi:10.1137/17M1135566

Evaluation neuer Exoskelettmechanismen in OpenSim. Bachelorarbeit
Butzer, J.
2018

Operational experience and commissioning of the Belle II vertex detector
Schwenker, B.; Abudinén, F.; Ackermann, K.; Ahlburg, P.; Aihara, H.; Albalawi, M.; Alonso, O.; Andricek, L.; Ayad, R.; Aziz, T.; Babu, V.; Bacher, S.; Bahinipati, S.; Bai, Y.; Barberio, E.; u. a.
2018. Collaborations, SVD (Hrsg.), 27th International Workshop on Vertex Detectors (VERTEX 2018), Chennai, IND, October 22-28, 2018, Scuola Internazionale Superiore di Studi Avanzati (SISSA)

La prima infrastruttura di data management per le nanoscienze
Aversa, R.; Cozzini, S.
2018. Conferenza GARR 2018 - Data (R)evolution - Selected Papers, Cagliari, Italy, 3-5 ottobre 2018, 26–29, Consortium GARR. doi:10.26314/GARR-Conf18-proceedings-04

D9.8: Final Report on Provision of Staging Support
Krauß, P.; Jankowski, M.; Kennedy, J. A.
2018. The EUDAT2020 Consortium. doi:10.5445/IR/1000096018

Analysis of Job Metadata for Enhanced Wall Time Prediction
Soysal, M.; Berghoff, M.; Streit, A.
2018. JSSPP (2018), Vancouver, Kanada, 21.–25. Mai 2018

Batch Job Scheduling Using Enhanced Walltime Prediction
Klusáček, D.; Soysal, M.
2018. CGW Workshop ’18 (CGW’18), Kraków, PL, 22-24 October 2018, AGH

Komplexe Modellierung: Trump gegen die Wissenschaft – Gibt es den Klimawandel wirklich?
Hattebuhr, M.; Frank, M.; Roeckerath, C.
2018. Beiträge zum Mathematikunterricht 2018. Bd.4, 731–734, WTM Verlag für wissenschaftliche Texte und Medien

Data Protection Impact Assessment – an initial guide for communities
Hardt, M.; Stevanovic, U.
2018. GÉANT

Expression of REFEDS RAF assurance components for identities derived from social media accounts
Hardt, M.; Stevanovic, U.
2018. GÉANT

Preliminary Policy Recommendations for the LS AAI (application to R&S and CoCo)
Hardt, M.; Stevanovic, U.
2018. GÉANT

Guidelines on stepping up the authentication component in AAIs implementing the AARC BPA
Stevanovic, U.
2018. (M. Hardt, Hrsg.), GÉANT. doi:10.5281/zenodo.1251671

Guideline on the exchange of specific assurance information between Infrastructures
Hardt, M.; Stevanovic, U.
2018. GÉANT

Guideline on the exchange of specific assurance information between Infrastructures (AARC-G021)
Stevanovic, U.; Hardt, M.
2018. GÉANT. doi:10.5281/zenodo.1173558

Federated Identity Management for Research Collaborations
Atherton, C. J.; Barton, T.; Basney, J.; Broeder, D.; Costa, A.; Daalen, M. van; Dyke, S.; Elbers, W.; Enell, C.-F.; Fasanelli, E. M. V.; Fernandes, J.; Florio, L.; Gietz, P.; Groep, D. L.; Junker, M. B.; u. a.
2018. doi:10.5281/zenodo.1307551

Komplexe Modellierung: Wie funktionieren eigentlich Animationsfilme und was hat das mit Mathe zu tun?
Wohak, K.; Frank, M.; Roeckerath, C.
2018. Beiträge zum Mathematikunterricht 2018. Bd.4, 2023–2026, WTM Verlag für wissenschaftliche Texte und Medien

Komplexe Modellierung: Wie funktionieren eigentlich Animationsfilme und was hat das mit Mathe zu tun?
Wohak, K.; Frank, M.; Roeckerath, C.
2018. 3. Gemeinsame Jahrestagung der Deutschen Mathematiker-Vereinigung (DMV) und der Gesellschaft für Didaktik der Mathematik (GDM 2018), Paderborn, Deutschland, 5.–9. März 2018

Efficient ray-tracing with real weather data
Richter, P.; Tinnes, J.; Schwarzbözl, P.; Rong, A.; Frank, M.
2018. SolarPACES 2017 : International Conference on Concentrating Solar Power and Chemical Energy Systems. Ed.: R. Mancilla, 210014, American Institute of Physics (AIP). doi:10.1063/1.5067216

SunFlower: A new solar tower simulation method for use in field layout optimization
Richter, P.; Heiming, G.; Lukas, N.; Frank, M.
2018. SolarPACES 2017 : International Conference on Concentrating Solar Power and Chemical Energy Systems. Ed.: R. Mancilla, 210015, American Institute of Physics (AIP). doi:10.1063/1.5067217

Towards reduction of computational cost for large-scale combustion modelling with a multi-regional concept
Zhang, F.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.
2018. Progress in computational fluid dynamics, 18 (6), 333–346. doi:10.1504/PCFD.2018.096616

Towards HS17
Alef, M.
2018. GDB (2018), Genf, Schweiz, 12. Juni 2018

Summary pre-GDB - CPU Benchmarking WG
Alef, M.; Giordano, D.; Michelotto, M.
2018. GDB (2018), Genf, Schweiz, 13. Juni 2018

CPU Benchmarking WG - activities and plans
Alef, M.; Giordano, D.; Michelotto, M.
2018. GDB (2018), Genf, Schweiz, 18. Juli 2018

CPU Benchmarking WG - activities and plans
Alef, M.; Giordano, D.; Michelotto, M.
2018. WLCG-MB (2018), Genf, Schweiz, 17. Juli 2018

Benchmarking Working Group - A status report
Alef, M.; Giordano, D.; Michelotto, M.
2018. HEPiX Spring Workshop (2018), Madison, WI, USA, 14.–18. Mai 2018

Benchmarking Update Oct 2018
Alef, M.; Giordano, D.; Michelotto, M.
2018. HEPiX Autumn/Fall Workshop (2018), Barcelona, Spanien, 8.–12. Oktober 2018