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67 Publications


2023 | Preprint | LibreCat-ID: 51158 | OA
F. Philipp, M. Schaller, K. Worthmann, S. Peitz, and F. Nüske, “Error analysis of kernel EDMD for prediction and control in the Koopman  framework,” arXiv:2312.10460. 2023.
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2023 | Preprint | LibreCat-ID: 46578 | OA
M. Bernreuther et al., “Multiobjective Optimization of Non-Smooth PDE-Constrained Problems,” arXiv:2308.01113. 2023.
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2023 | Conference Paper | LibreCat-ID: 54838
S. Boshoff et al., “Hybrid control of interconnected power converters using both expert-driven droop and data-driven reinforcement learning approaches,” in IEEE Power and Energy Student Summit (PESS), 2023, pp. 124–129.
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2023 | Conference Paper | LibreCat-ID: 54839
M. Meyer et al., “ElectricGrid.jl – Automated modeling of decentralized electrical energy grids,” in IEEE Power and Energy Student Summit (PESS), 2023, pp. 112–117.
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2023 | Preprint | LibreCat-ID: 42160 | OA
S. Werner and S. Peitz, “Learning a model is paramount for sample efficiency in reinforcement  learning control of PDEs,” arXiv:2302.07160. 2023.
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2023 | Journal Article | LibreCat-ID: 27426 | OA
B. Gebken, K. Bieker, and S. Peitz, “On the structure of regularization paths for piecewise differentiable regularization terms,” Journal of Global Optimization, vol. 85, no. 3, pp. 709–741, 2023, doi: 10.1007/s10898-022-01223-2.
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2023 | Conference Paper | LibreCat-ID: 30125 | OA
M. Schaller, K. Worthmann, F. Philipp, S. Peitz, and F. Nüske, “Towards reliable data-based optimal and predictive control using extended DMD,” in IFAC-PapersOnLine, 2023, vol. 56, no. 1, pp. 169–174, doi: 10.1016/j.ifacol.2023.02.029.
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2023 | Preprint | LibreCat-ID: 46579 | OA
S. Peitz, H. Harder, F. Nüske, F. Philipp, M. Schaller, and K. Worthmann, “Partial observations, coarse graining and equivariance in Koopman  operator theory for large-scale dynamical systems,” arXiv:2307.15325. 2023.
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2023 | Journal Article | LibreCat-ID: 23428 | OA
F. Nüske, S. Peitz, F. Philipp, M. Schaller, and K. Worthmann, “Finite-data error bounds for Koopman-based prediction and control,” Journal of Nonlinear Science, vol. 33, Art. no. 14, 2023, doi: 10.1007/s00332-022-09862-1.
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2023 | Journal Article | LibreCat-ID: 21600
M. Dellnitz et al., “Efficient time stepping for numerical integration using reinforcement  learning,” SIAM Journal on Scientific Computing, vol. 45, no. 2, pp. A579–A595, 2023, doi: 10.1137/21M1412682.
LibreCat | Files available | DOI | Download (ext.) | arXiv
 

2023 | Journal Article | LibreCat-ID: 46784 | OA
O. Wallscheid et al., “ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids,” Journal of Open Source Software, vol. 8, no. 89, Art. no. 5616, 2023, doi: 10.21105/joss.05616.
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2023 | Conference Paper | LibreCat-ID: 46813 | OA
M. C. Wohlleben, L. Muth, S. Peitz, and W. Sextro, “Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits,” 2023, doi: 10.1002/pamm.202300039.
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2022 | Book Chapter | LibreCat-ID: 16296 | OA
S. Banholzer, B. Gebken, M. Dellnitz, S. Peitz, and S. Volkwein, “ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation,” in Non-Smooth and Complementarity-Based Distributed Parameter Systems, H. Michael, H. Roland, K. Christian, U. Michael, and U. Stefan, Eds. Cham: Springer, 2022, pp. 43–76.
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2022 | Book Chapter | LibreCat-ID: 30294
S. Peitz, M. Dellnitz, and S. Bannenberg, “Efficient Virtual Design and Testing of Autonomous Vehicles,” in German Success Stories in Industrial Mathematics, vol. 35, H. G. Bock, K.-H. Küfer, P. Maas, A. Milde, and V. Schulz, Eds. Cham: Springer International Publishing, 2022.
LibreCat | DOI
 

2022 | Journal Article | LibreCat-ID: 29673 | OA
S. Klus, F. Nüske, and S. Peitz, “Koopman analysis of quantum systems,” Journal of Physics A: Mathematical and Theoretical, vol. 55, no. 31, p. 314002, 2022, doi: 10.1088/1751-8121/ac7d22.
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2022 | Preprint | LibreCat-ID: 33150 | OA
M. B. Berkemeier and S. Peitz, “Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients,” arXiv:2208.12094. 2022.
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2022 | Journal Article | LibreCat-ID: 20731 | OA
K. Bieker, B. Gebken, and S. Peitz, “On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 11, pp. 7797–7808, 2022, doi: 10.1109/TPAMI.2021.3114962.
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2022 | Book Chapter | LibreCat-ID: 29727
M. C. Wohlleben, A. Bender, S. Peitz, and W. Sextro, “Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction,” in Machine Learning, Optimization, and Data Science, Cham: Springer International Publishing, 2022.
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2021 | Journal Article | LibreCat-ID: 21337 | OA
M. B. Berkemeier and S. Peitz, “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models,” Mathematical and Computational Applications, vol. 26, no. 2, 2021.
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2021 | Journal Article | LibreCat-ID: 16867 | OA
B. Gebken and S. Peitz, “An efficient descent method for locally Lipschitz multiobjective optimization problems,” Journal of Optimization Theory and Applications, vol. 188, pp. 696–723, 2021.
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