R. Herkert. Software, (2024)Related to: R. Herkert, P. Buchfink, B. Haasdonk, J. Rettberg, J. Fehr. (2024), "Error Analysis of Randomized Symplectic Model Order Reduction for Hamiltonian systems". arXiv: 2405.10465.
C. Homs Pons, and R. Lautenschlager. Software, (2024)Related to: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models, submitted to GAMM Mitteilungen.
J. Rettberg, D. Wittwar, and R. Herkert. Software, (2023)Related to: Rettberg, J.; Wittwar, D.; Buchfink, P.; Brauchler, A.; Ziegler, P.; Fehr, J.; Haasdonk, B.: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar. Mathematical and Computer Modelling of Dynamical Systems, 2023, Vol. 29, No. 1, 116-148. doi: 10.1080/13873954.2023.2173238.
J. Kühnert, D. Göddeke, and M. Herschel. 13th International Workshop on Theory and Practice of Provenance, page 1-4. Red Hook, Curran Associates, Inc., (2021)
J. Schmalfuss, C. Riethmüller, M. Altenbernd, K. Weishaupt, and D. Göddeke. Presentations and Plenary videos to 9th edition of the International Conference on Computational Methods for Coupled Problems in Science and Engineering (COUPLED PROBLEMS 2021), Barcelona, Scipedia, S.L., (2021)
F. Huber, P. Bürkner, D. Göddeke, and 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).
R. Herkert. Software, (2023)Related to: R. Herkert, P. Buchfink, B. Haasdonk, J. Rettberg, J. Fehr: Randomized Symplectic Model Order Reduction for Hamiltonian Systemsm 2023. arXiv: 2303.04036.
J. Rettberg, D. Wittwar, P. Buchfink, A. Brauchler, P. Ziegler, J. Fehr, and B. Haasdonk. Dataset, (2023)Related to: Rettberg, J.; Wittwar, D.; Buchfink, P.; Brauchler, A.; Ziegler, P.; Fehr, J.; Haasdonk, B.: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar. Mathematical and Computer Modelling of Dynamical Systems, 2023. doi: 10.1080/13873954.2023.2173238.
D. Holzmüller, V. Zaverkin, J. Kästner, and I. Steinwart. Software, (2023)Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2023. arXiv: 2203.09410.
J. Fehr, D. Grunert, A. Bhatt, and B. Haasdonk. 89th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), 18, 1, page e201800275. Wiley, (2018)
V. Zaverkin, D. Holzmüller, L. Bonfirraro, and J. Kästner. Dataset, (2023)Related to: Viktor Zaverkin, David Holzmüller, Luca Bonfirraro, Johannes Kästner. Transfer learning for chemically accurate interatomic neural network potentials, Phys. Chem. Chem. Phys., 2023, 25, 5383-5396. doi: 10.1039/D2CP05793J.
A. Bhatt, J. Fehr, D. Grunert, and B. Haasdonk. IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018, volume 36 of IUTAM Bookseries, page 95-110. Springer, (2019)
S. Shuva, P. Buchfink, O. Röhrle, and B. Haasdonk. Large-Scale Scientific Computing : 13th International Conference, LSSC 2021, Sozopol, Bulgaria, June 7-11, 2021, Revised Selected Papers, 13127, page 402-409. Cham, Springer, (2021)
S. Burbulla, M. Hörl, and C. Rohde. Software, (2022)Related to: S. Burbulla, M. Hörl, and C. Rohde (2022). "Flow in Porous Media with Fractures of Varying Aperture." Submitted for publication. doi: 10.48550/arXiv.2207.09301.
S. Burbulla, M. Hörl, and C. Rohde. Dataset, (2022)Related to: S. Burbulla, M. Hörl, and C. Rohde (2022). "Flow in Porous Media with Fractures of Varying Aperture." Submitted for publication. doi: 10.48550/arXiv.2207.09301.
C. Beschle, and A. Barth. Software, (2022)Related to: Hägele, David, Schulz, Christoph, Beschle, Cedric, Booth, Hannah, Butt, Miriam, Barth, Andrea, Deussen, Oliver, & Weiskopf, Daniel (2022). Uncertainty visualization: Fundamentals and recent developments. it - Information Technology 64(4-5), 121-132. doi: 10.1515/itit-2022-0033.
D. Holzmüller, V. Zaverkin, J. Kästner, and I. Steinwart. Software, (2022)Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2022. arXiv: 2203.09410.