T. Schrader, D. Schneider, und B. Uekermann. Software, (2023)Related to: David Schneider, Timo Pierre Schrader, Benjamin Uekermann: "Data-Parallel Radial-Basis Function Interpolation in preCICE", International Conference on Computational Methods for Coupled Problems in Science and Engineering 2023 (in preparation).
F. Huber, P. Bürkner, D. Göddeke, und M. Schulte. Dataset, (2023)Related to: Huber, Felix; Bürkner, Paul-Christian; Göddeke, Dominik; Schulte, MiriamKnowledge-Based Modeling of Simulation Behavior for Bayesian OptimizationComputational Mechanics (submitted).
T. Pollinger. Dataset, (2023)Related to: Leveraging the compute power of two HPC systems for higher-dimensional grid-based simulations with the widely-distributed sparse grid combination technique (submitted).
B. Xiong, S. Zhu, M. Nayyeri, C. Xu, S. Pan, C. Zhou, und S. Staab. KDD '22 : Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Seite 2130-2139. New York, Association for Computing Machinery, (2022)
B. Xiong, S. Zhu, N. Potyka, S. Pan, C. Zhou, und S. Staab. Advances in Neural Information Processing Systems 35 (NeurIPS 2022), Seite 3488-3501. Red Hook, Curran Associates, Inc., (2022)
J. Kühnert, D. Göddeke, und M. Herschel. 13th International Workshop on Theory and Practice of Provenance, Seite 1-4. Red Hook, Curran Associates, Inc., (2021)
S. Oppold, und M. Herschel. TaPP '22 : Proceedings of the 14th International Workshop on the Theory and Practice of Provenance, New York, Association for Computing Machinery, (2022)
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
M. Heene, und D. Pflüger. Parallel Computing: On the Road to Exascale, Proceedings of the International Conference on Parallel Computing, ParCo 2015, 27, Seite 339-348. IOS Press, (2016)
M. Breyer, A. Van Craen, und D. Pflüger. IWOCL '23: Proceedings of the 2023 International Workshop on OpenCL, Seite 1-12. Association for Computing Machinery, (2023)
S. Hirschmann, D. Pflüger, und C. Glass. 2016 IEEE 23rd International Conference on High Performance Computing Workshops (HiPCW), Seite 130-141. IEEE, (2016)
I. Desai, E. Scheurer, C. Bringedal, und B. Uekermann. Software, (2023)Related to: Desai, Ishaan, & Bringedal, Carina & Uekermann, Benjamin. A flexible software approach to simulate two-scale coupled problems. ECCOMAS Congress 2022. doi: 10.23967/eccomas.2022.037.
Y. Li, P. Hirmer, C. Stach, und B. Mitschang. IoT '22 : Proceedings of the 12th International Conference on the Internet of Things, Seite 135-138. New York, Association for Computing Machinery, (2022)
M. Heck, C. Becker, und V. Deutscher. Proceedings of the 56th Hawaii International Conference on System Sciences, Seite 6820-6829. Honolulu, Department of IT Management, Shidler College of Business, University of Hawaii, (2023)
C. Homs Pons, und R. Lautenschlager. Software, (2024)Related to: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models, submitted to GAMM Mitteilungen.
H. Geppert, S. Bhowmik, und K. Rothermel. GRADES-NDA '21 : Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), Seite 6. New York, Association for Computing Machinery, (2021)
H. Kschidock. Dataset, (2024)Related to: Kschidock, Helena: Development of an Euler-Lagrangian framework for point-particle tracking to enable efficient multiscale simulations of complex flows.Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik, Masterarbeit Nr. 70 (2023). doi: 10.18419/opus-13813.
I. Desai, C. Bringedal, und B. Uekermann. The 8th European Congress on Computational Methods in Applied Sciences and Engineering : ECCOMAS Congress 2022, Barcelona, Scipedia, (2022)
J. Pelzer. Software, (2024)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Software, (2024)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
F. Lindner, M. Mehl, und B. Uekermann. Proceedings of the VII International Conference on Coupled Problems in Science and Engineering, Seite 50-61. Barcelona, CIMNE, (2017)
M. Behringer, und P. Hirmer. Proceedings of the 35th International Conference on Scientific and Statistical Database Management, Seite 25. New York, NY, United States, Association for Computing Machinery, (2023)
J. Kässinger, H. Trötsch, F. Dürr, und J. Edinger. Proceedings of the Int'l ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems, Seite 181-190. Association for Computing Machinery, (2023)
M. Heck, J. Jeong, und C. Becker. Proceedings of the 25th International Conference on Multimodal Interaction, Seite 243-252. Association for Computing Machinery, (2023)
M. Takamoto, T. Praditia, R. Leiteritz, D. MacKinlay, F. Alesiani, D. Pflüger, und M. Niepert. Dataset, (2022)Related to: Takamoto, M., Praditia, T., Leiteritz, R., MacKinlay, D., Alesiani, F., Pflüger, D. and Niepert, M.: PDEBench: An Extensive Benchmark for Scientific Machine Learning. submitted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks.
F. Huber, P. Bürkner, D. Göddeke, und M. Schulte. Dataset, (2023)Related to: Huber, Felix; Bürkner, Paul-Christian; Göddeke, Dominik; Schulte, MiriamKnowledge-Based Modeling of Simulation Behavior for Bayesian OptimizationComputational Mechanics (submitted).
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
M. Takamoto, T. Praditia, R. Leiteritz, D. MacKinlay, F. Alesiani, D. Pflüger, und M. Niepert. Dataset, (2022)Related to: Takamoto, M., Praditia, T., Leiteritz, R., MacKinlay, D., Alesiani, F., Pflüger, D. and Niepert, M.: PDEBench: An Extensive Benchmark for Scientific Machine Learning. submitted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks. arXiv: 2210.07182.
A. Baier, und D. Frank. Software, (2023)Related to: Baier, Alexandra, Boukhers, Zeyd, & Staab, Steffen (2021). Hybrid Physics and Deep Learning Model for Interpretable Vehicle State Prediction. ArXiv, abs/2103.06727. arXiv: abs/2103.06727.