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282 Publications


2021 | Preprint | LibreCat-ID: 21600
Dellnitz, Michael, et al. “Efficient Time Stepping for Numerical Integration Using Reinforcement  Learning.” ArXiv:2104.03562, 2021.
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2021 | Journal Article | LibreCat-ID: 16295
Gebken, Bennet, and Sebastian Peitz. “Inverse Multiobjective Optimization: Inferring Decision Criteria from Data.” Journal of Global Optimization, vol. 80, Springer, 2021, pp. 3–29, doi:10.1007/s10898-020-00983-z.
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2021 | Preprint | LibreCat-ID: 23428
Nüske, Feliks, et al. “Finite-Data Error Bounds for Koopman-Based Prediction and Control.” ArXiv:2108.07102, 2021.
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2021 | Preprint | LibreCat-ID: 21199
Peitz, Sebastian, and Katharina Bieker. “On the Universal Transformation of Data-Driven Models to Control Systems.” ArXiv:2102.04722, 2021.
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2021 | Conference Paper | LibreCat-ID: 22894
Offen, Christian, and Sina Ober-Blöbaum. Bifurcation Preserving Discretisations of Optimal Control Problems.
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2021 | Journal Article | LibreCat-ID: 16867
Gebken, Bennet, and Sebastian Peitz. “An Efficient Descent Method for Locally Lipschitz Multiobjective Optimization Problems.” Journal of Optimization Theory and Applications, vol. 188, 2021, pp. 696–723, doi:10.1007/s10957-020-01803-w.
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2021 | Journal Article | LibreCat-ID: 21195
Goelz, Christian, et al. “Electrophysiological Signatures of Dedifferentiation Differ between Fit and Less Fit Older Adults.” Cognitive Neurodynamics, 2021, doi:10.1007/s11571-020-09656-9.
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2021 | Journal Article | LibreCat-ID: 24170
Klus, Stefan, et al. “Symmetric and Antisymmetric Kernels for Machine Learning Problems in Quantum Physics and Chemistry.” Machine Learning: Science and Technology, 045016, 2021, doi:10.1088/2632-2153/ac14ad.
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2021 | Journal Article | LibreCat-ID: 20731
Bieker, Katharina, et al. “On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE, 2021, doi:10.1109/TPAMI.2021.3114962.
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2021 | Preprint | LibreCat-ID: 23382
Offen, Christian, and Sina Ober-Blöbaum. Symplectic Integration of Learned Hamiltonian Systems.
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