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63 Publications
2024 | Preprint | LibreCat-ID: 51160 |
Philipp, Friedrich M., et al. “Extended Dynamic Mode Decomposition: Sharp Bounds on the Sample Efficiency.” ArXiv:2402.02494, 2024.
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| arXiv
2024 | Journal Article | LibreCat-ID: 46019 |
Sonntag, Konstantin, and Sebastian Peitz. “Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems.” Journal of Optimization Theory and Applications, Springer, 2024, doi:10.1007/s10957-024-02389-3.
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2024 | Preprint | LibreCat-ID: 51334 |
Sonntag, Konstantin, et al. “A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces.” ArXiv:2402.06376, 2024.
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| arXiv
2024 | Journal Article | LibreCat-ID: 40171 |
Peitz, Sebastian, et al. “Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning.” Physica D: Nonlinear Phenomena, vol. 461, Elsevier, 2024, p. 134096, doi:10.1016/j.physd.2024.134096.
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2024 | Journal Article | LibreCat-ID: 33461 |
Otto, Samuel E., et al. “Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories.” SIAM Journal on Applied Dynamical Systems, vol. 23, no. 1, SIAM, 2024, pp. 885–923, doi:10.1137/22M1523601.
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| arXiv
2024 | Journal Article | LibreCat-ID: 38031 |
Philipp, Friedrich, et al. “Error Bounds for Kernel-Based Approximations of the Koopman Operator.” Applied and Computational Harmonic Analysis , vol. 71, 101657, Springer , 2024, doi:10.1016/j.acha.2024.101657.
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| arXiv
2024 | Preprint | LibreCat-ID: 53793 |
Harder, Hans, and Sebastian Peitz. Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines.
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2024 | Preprint | LibreCat-ID: 52758
Harder, Hans, and Sebastian Peitz. On the Continuity and Smoothness of the Value Function in Reinforcement Learning and Optimal Control. 2024.
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2023 | Journal Article | LibreCat-ID: 21199 |
Peitz, Sebastian, and Katharina Bieker. “On the Universal Transformation of Data-Driven Models to Control Systems.” Automatica, vol. 149, 110840, Elsevier, 2023, doi:10.1016/j.automatica.2022.110840.
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2023 | Preprint | LibreCat-ID: 42160 |
Werner, Stefan, and Sebastian Peitz. “Learning a Model Is Paramount for Sample Efficiency in Reinforcement Learning Control of PDEs.” ArXiv:2302.07160, 2023.
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| arXiv
2023 | Journal Article | LibreCat-ID: 27426 |
Gebken, Bennet, et al. “On the Structure of Regularization Paths for Piecewise Differentiable Regularization Terms.” Journal of Global Optimization, vol. 85, no. 3, 2023, pp. 709–41, doi:10.1007/s10898-022-01223-2.
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2023 | Conference Paper | LibreCat-ID: 30125 |
Schaller, Manuel, et al. “Towards Reliable Data-Based Optimal and Predictive Control Using Extended DMD.” IFAC-PapersOnLine, vol. 56, no. 1, 2023, pp. 169–74, doi:10.1016/j.ifacol.2023.02.029.
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| arXiv
2023 | Preprint | LibreCat-ID: 46579 |
Peitz, Sebastian, et al. “Partial Observations, Coarse Graining and Equivariance in Koopman Operator Theory for Large-Scale Dynamical Systems.” ArXiv:2307.15325, 2023.
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| arXiv
2023 | Journal Article | LibreCat-ID: 23428 |
Nüske, Feliks, et al. “Finite-Data Error Bounds for Koopman-Based Prediction and Control.” Journal of Nonlinear Science, vol. 33, 14, 2023, doi:10.1007/s00332-022-09862-1.
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2023 | Preprint | LibreCat-ID: 46649 |
Hotegni, Sedjro Salomon, et al. “Multi-Objective Optimization for Sparse Deep Neural Network Training.” ArXiv:2308.12243, 2023.
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| arXiv
2023 | Journal Article | LibreCat-ID: 21600
Dellnitz, Michael, et al. “Efficient Time Stepping for Numerical Integration Using Reinforcement Learning.” SIAM Journal on Scientific Computing, vol. 45, no. 2, 2023, pp. A579–95, doi:10.1137/21M1412682.
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| arXiv
2023 | Journal Article | LibreCat-ID: 46784 |
Wallscheid, Oliver, 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, 5616, The Open Journal, 2023, doi:10.21105/joss.05616.
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2023 | Conference Paper | LibreCat-ID: 46813 |
Wohlleben, Meike Claudia, et al. “Transferability of a Discrepancy Model for the Dynamics of Electromagnetic Oscillating Circuits.” Proceedings in Applied Mathematics and Mechanics, Wiley, 2023, doi:10.1002/pamm.202300039.
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2023 | Preprint | LibreCat-ID: 48502 |
Peitz, Sebastian, et al. Accelerating the Analysis of Optical Quantum Systems Using the Koopman Operator. 2023.
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2023 | Preprint | LibreCat-ID: 51159 |
Amakor, Augustina Chidinma, et al. “A Multiobjective Continuation Method to Compute the Regularization Path of Deep Neural Networks.” ArXiv, 2023.
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2023 | Preprint | LibreCat-ID: 51158 |
Philipp, Friedrich, et al. “Error Analysis of Kernel EDMD for Prediction and Control in the Koopman Framework.” ArXiv:2312.10460, 2023.
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| arXiv
2023 | Preprint | LibreCat-ID: 32447 |
Sonntag, Konstantin, and Sebastian Peitz. “Fast Convergence of Inertial Multiobjective Gradient-like Systems with Asymptotic Vanishing Damping.” ArXiv:2307.00975, 2023.
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| arXiv
2023 | Preprint | LibreCat-ID: 46578 |
Bernreuther, Marco, et al. “Multiobjective Optimization of Non-Smooth PDE-Constrained Problems.” ArXiv:2308.01113, 2023.
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| arXiv
2022 | Book Chapter | LibreCat-ID: 16296 |
Banholzer, Stefan, et al. “ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation.” Non-Smooth and Complementarity-Based Distributed Parameter Systems, edited by Hintermüller Michael et al., Springer, 2022, pp. 43–76, doi:10.1007/978-3-030-79393-7_3.
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2022 | Book Chapter | LibreCat-ID: 30294
Peitz, Sebastian, et al. “Efficient Virtual Design and Testing of Autonomous Vehicles.” German Success Stories in Industrial Mathematics, edited by H. G. Bock et al., vol. 35, Springer International Publishing, 2022, doi:10.1007/978-3-030-81455-7_23.
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2022 | Journal Article | LibreCat-ID: 29673 |
Klus, Stefan, et al. “Koopman Analysis of Quantum Systems.” Journal of Physics A: Mathematical and Theoretical, vol. 55, no. 31, IOP Publishing Ltd., 2022, p. 314002, doi:10.1088/1751-8121/ac7d22.
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| arXiv
2022 | Preprint | LibreCat-ID: 33150 |
Berkemeier, Manuel Bastian, and Sebastian Peitz. “Multi-Objective Trust-Region Filter Method for Nonlinear Constraints Using Inexact Gradients.” ArXiv:2208.12094, 2022.
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| arXiv
2022 | 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, vol. 44, no. 11, IEEE, 2022, pp. 7797–808, doi:10.1109/TPAMI.2021.3114962.
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2022 | Book Chapter | LibreCat-ID: 29727
Wohlleben, Meike Claudia, et al. “Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction.” Machine Learning, Optimization, and Data Science, Springer International Publishing, 2022, doi:10.1007/978-3-030-95470-3_8.
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2021 | Journal Article | LibreCat-ID: 21337 |
Berkemeier, Manuel Bastian, and Sebastian Peitz. “Derivative-Free Multiobjective Trust Region Descent Method Using Radial Basis Function Surrogate Models.” Mathematical and Computational Applications, vol. 26, no. 2, 31, 2021, doi:10.3390/mca26020031.
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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: 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 | Journal Article | LibreCat-ID: 16294 |
Ober-Blöbaum, Sina, and Sebastian Peitz. “Explicit Multiobjective Model Predictive Control for Nonlinear Systems with Symmetries.” International Journal of Robust and Nonlinear Control, vol. 31(2), 2021, pp. 380–403, doi:10.1002/rnc.5281.
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2020 | Book Chapter | LibreCat-ID: 17411
Flaßkamp, Kathrin, et al. “Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach.” Advances in Dynamics, Optimization and Computation, edited by Oliver Junge et al., Springer, 2020, doi:10.1007/978-3-030-51264-4_9.
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2020 | Journal Article | LibreCat-ID: 10596
Schütze, Oliver, et al. “Pareto Explorer: A Global/Local Exploration Tool for Many-Objective Optimization Problems.” Engineering Optimization, vol. 52, no. 5, 2020, pp. 832–55, doi:10.1080/0305215x.2019.1617286.
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2020 | Journal Article | LibreCat-ID: 16288
Klus, Stefan, et al. “Data-Driven Approximation of the Koopman Generator: Model Reduction, System Identification, and Control.” Physica D: Nonlinear Phenomena, vol. 406, 132416, 2020, doi:10.1016/j.physd.2020.132416.
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2020 | Book Chapter | LibreCat-ID: 16289
Peitz, Sebastian, and Stefan Klus. “Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator.” Lecture Notes in Control and Information Sciences, vol. 484, Springer, 2020, pp. 257–82, doi:10.1007/978-3-030-35713-9_10.
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2020 | Journal Article | LibreCat-ID: 16290 |
Bieker, Katharina, et al. “Deep Model Predictive Flow Control with Limited Sensor Data and Online Learning.” Theoretical and Computational Fluid Dynamics, vol. 34, 2020, pp. 577–591, doi:10.1007/s00162-020-00520-4.
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2020 | Journal Article | LibreCat-ID: 16309
Peitz, Sebastian, et al. “Data-Driven Model Predictive Control Using Interpolated Koopman Generators.” SIAM Journal on Applied Dynamical Systems, vol. 19, no. 3, 2020, pp. 2162–93, doi:10.1137/20M1325678.
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2020 | Journal Article | LibreCat-ID: 16297
Hernández Castellanos, Carlos Ignacio, et al. “Explicit Multi-Objective Model Predictive Control for Nonlinear Systems Under Uncertainty.” International Journal of Robust and Nonlinear Control, vol. 30(17), 2020, pp. 7593–618, doi:10.1002/rnc.5197.
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2019 | Journal Article | LibreCat-ID: 10593
Peitz, Sebastian, and Stefan Klus. “Koopman Operator-Based Model Reduction for Switched-System Control of PDEs.” Automatica, vol. 106, 2019, pp. 184–91, doi:10.1016/j.automatica.2019.05.016.
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2019 | Journal Article | LibreCat-ID: 10595
Gebken, Bennet, et al. “On the Hierarchical Structure of Pareto Critical Sets.” Journal of Global Optimization, vol. 73, no. 4, 2019, pp. 891–913, doi:10.1007/s10898-019-00737-6.
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2019 | Conference Paper | LibreCat-ID: 10597
Hanke, Soren, et al. “Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous Motor Application with Online Least Squares System Identification.” 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE), 2019, doi:10.1109/precede.2019.8753313.
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2019 | Conference Paper | LibreCat-ID: 29636
Hanke, Sören, et al. “Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous Motor Application with Online Least Squares System Identification.” 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE), 2019, pp. 1–6.
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2018 | Preprint | LibreCat-ID: 21634 |
Hanke, Sören, et al. “Koopman Operator-Based Finite-Control-Set Model Predictive Control for Electrical Drives.” ArXiv:1804.00854, 2018.
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2018 | Book Chapter | LibreCat-ID: 22796
Kummert, Franz, et al. “Eingesetzte wissenschaftliche Methoden.” Ressourceneffiziente Selbstoptimierende Wäscherei – Ergebnisse des ReSerW-Projekts, edited by Ansgar Trächtler, Springer, 2018.
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2018 | Conference Paper | LibreCat-ID: 8750
Gebken, Bennet, et al. “A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems.” Numerical and Evolutionary Optimization – NEO 2017, 2018, doi:10.1007/978-3-319-96104-0_2.
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2018 | Journal Article | LibreCat-ID: 8751 |
Peitz, Sebastian, and Michael Dellnitz. “A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models, Feedback Control and Objective Reduction.” Mathematical and Computational Applications, vol. 23, no. 2, 2018, doi:10.3390/mca23020030.
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2018 | Book Chapter | LibreCat-ID: 8754
Beermann, Dennis, et al. “Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition.” Reduced-Order Modeling (ROM) for Simulation and Optimization, 2018, pp. 47–72, doi:10.1007/978-3-319-75319-5_3.
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2018 | Journal Article | LibreCat-ID: 8755
Klus, Stefan, et al. “Tensor-Based Dynamic Mode Decomposition.” Nonlinearity, vol. 31, no. 7, 2018, pp. 3359–80, doi:10.1088/1361-6544/aabc8f.
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