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64 Publications


2023 | Preprint | LibreCat-ID: 51159 | OA
Amakor, Augustina Chidinma, Konstantin Sonntag, and Sebastian Peitz. “A Multiobjective Continuation Method to Compute the Regularization Path of Deep Neural Networks.” ArXiv, 2023.
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2023 | Preprint | LibreCat-ID: 51158 | OA
Philipp, Friedrich, Manuel Schaller, Karl Worthmann, Sebastian Peitz, and Feliks Nüske. “Error Analysis of Kernel EDMD for Prediction and Control in the Koopman  Framework.” ArXiv:2312.10460, 2023.
LibreCat | Download (ext.) | arXiv
 

2023 | Preprint | LibreCat-ID: 32447 | OA
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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2023 | Preprint | LibreCat-ID: 46578 | OA
Bernreuther, Marco, Michael Dellnitz, Bennet Gebken, Georg Müller, Sebastian Peitz, Konstantin Sonntag, and Stefan Volkwein. “Multiobjective Optimization of Non-Smooth PDE-Constrained Problems.” ArXiv:2308.01113, 2023.
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2022 | Book Chapter | LibreCat-ID: 16296 | OA
Banholzer, Stefan, Bennet Gebken, Michael Dellnitz, Sebastian Peitz, and Stefan Volkwein. “ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation.” In Non-Smooth and Complementarity-Based Distributed Parameter Systems, edited by Hintermüller Michael, Herzog Roland, Kanzow Christian, Ulbrich Michael, and Ulbrich Stefan, 43–76. Cham: Springer, 2022. https://doi.org/10.1007/978-3-030-79393-7_3.
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2022 | Book Chapter | LibreCat-ID: 30294
Peitz, Sebastian, Michael Dellnitz, and Sebastian Bannenberg. “Efficient Virtual Design and Testing of Autonomous Vehicles.” In German Success Stories in Industrial Mathematics, edited by H. G. Bock, K.-H. Küfer, P. Maas, A. Milde, and V. Schulz, Vol. 35. Mathematics in Industry. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-030-81455-7_23.
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2022 | Journal Article | LibreCat-ID: 29673 | OA
Klus, Stefan, Feliks Nüske, and Sebastian Peitz. “Koopman Analysis of Quantum Systems.” Journal of Physics A: Mathematical and Theoretical 55, no. 31 (2022): 314002. https://doi.org/10.1088/1751-8121/ac7d22.
LibreCat | DOI | Download (ext.) | arXiv
 

2022 | Preprint | LibreCat-ID: 33150 | OA
Berkemeier, Manuel Bastian, and Sebastian Peitz. “Multi-Objective Trust-Region Filter Method for Nonlinear Constraints Using Inexact Gradients.” ArXiv:2208.12094, 2022.
LibreCat | Download (ext.) | arXiv
 

2022 | Journal Article | LibreCat-ID: 20731 | OA
Bieker, Katharina, Bennet Gebken, and Sebastian Peitz. “On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 44, no. 11 (2022): 7797–7808. https://doi.org/10.1109/TPAMI.2021.3114962.
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2022 | Book Chapter | LibreCat-ID: 29727
Wohlleben, Meike Claudia, Amelie Bender, Sebastian Peitz, and Walter Sextro. “Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction.” In Machine Learning, Optimization, and Data Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-030-95470-3_8.
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2021 | Journal Article | LibreCat-ID: 21337 | OA
Berkemeier, Manuel Bastian, and Sebastian Peitz. “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models.” Mathematical and Computational Applications 26, no. 2 (2021). https://doi.org/10.3390/mca26020031.
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2021 | Journal Article | LibreCat-ID: 16867 | OA
Gebken, Bennet, and Sebastian Peitz. “An Efficient Descent Method for Locally Lipschitz Multiobjective Optimization Problems.” Journal of Optimization Theory and Applications 188 (2021): 696–723. https://doi.org/10.1007/s10957-020-01803-w.
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2021 | Journal Article | LibreCat-ID: 16295 | OA
Gebken, Bennet, and Sebastian Peitz. “Inverse Multiobjective Optimization: Inferring Decision Criteria from Data.” Journal of Global Optimization 80 (2021): 3–29. https://doi.org/10.1007/s10898-020-00983-z.
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2021 | Journal Article | LibreCat-ID: 16294 | OA
Ober-Blöbaum, Sina, and Sebastian Peitz. “Explicit Multiobjective Model Predictive Control for Nonlinear Systems  with Symmetries.” International Journal of Robust and Nonlinear Control 31(2) (2021): 380–403. https://doi.org/10.1002/rnc.5281.
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2020 | Book Chapter | LibreCat-ID: 17411
Flaßkamp, Kathrin, Sina Ober-Blöbaum, and Sebastian Peitz. “Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach.” In Advances in Dynamics, Optimization and Computation, edited by Oliver Junge, Oliver Schütze, Gary Froyland, Sina Ober-Blöbaum, and Kathrin Padberg-Gehle. Cham: Springer, 2020. https://doi.org/10.1007/978-3-030-51264-4_9.
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2020 | Journal Article | LibreCat-ID: 10596
Schütze, Oliver, Oliver Cuate, Adanay Martín, Sebastian Peitz, and Michael Dellnitz. “Pareto Explorer: A Global/Local Exploration Tool for Many-Objective Optimization Problems.” Engineering Optimization 52, no. 5 (2020): 832–55. https://doi.org/10.1080/0305215x.2019.1617286.
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2020 | Journal Article | LibreCat-ID: 16288
Klus, Stefan, Feliks Nüske, Sebastian Peitz, Jan-Hendrik Niemann, Cecilia Clementi, and Christof Schütte. “Data-Driven Approximation of the Koopman Generator: Model Reduction, System Identification, and Control.” Physica D: Nonlinear Phenomena 406 (2020). https://doi.org/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.” In Lecture Notes in Control and Information Sciences, 484:257–82. Lecture Notes in Control and Information Sciences. Cham: Springer, 2020. https://doi.org/10.1007/978-3-030-35713-9_10.
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2020 | Journal Article | LibreCat-ID: 16290 | OA
Bieker, Katharina, Sebastian Peitz, Steven L. Brunton, J. Nathan Kutz, and Michael Dellnitz. “Deep Model Predictive Flow Control with Limited Sensor Data and Online Learning.” Theoretical and Computational Fluid Dynamics 34 (2020): 577–591. https://doi.org/10.1007/s00162-020-00520-4.
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2020 | Journal Article | LibreCat-ID: 16309
Peitz, Sebastian, Samuel E. Otto, and Clarence W. Rowley. “Data-Driven Model Predictive Control Using Interpolated Koopman  Generators.” SIAM Journal on Applied Dynamical Systems 19, no. 3 (2020): 2162–93. https://doi.org/10.1137/20M1325678.
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