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64 Publications
2023 | Preprint | LibreCat-ID: 51159 | 
A multiobjective continuation method to compute the regularization path of deep neural networks
A.C. Amakor, K. Sonntag, S. Peitz, ArXiv (2023).
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A.C. Amakor, K. Sonntag, S. Peitz, ArXiv (2023).
2023 | Preprint | LibreCat-ID: 51158 |
Error analysis of kernel EDMD for prediction and control in the Koopman framework
F. Philipp, M. Schaller, K. Worthmann, S. Peitz, F. Nüske, ArXiv:2312.10460 (2023).
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F. Philipp, M. Schaller, K. Worthmann, S. Peitz, F. Nüske, ArXiv:2312.10460 (2023).
2023 | Preprint | LibreCat-ID: 32447 |
Fast Convergence of Inertial Multiobjective Gradient-like Systems with Asymptotic Vanishing Damping
K. Sonntag, S. Peitz, ArXiv:2307.00975 (2023).
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K. Sonntag, S. Peitz, ArXiv:2307.00975 (2023).
2023 | Preprint | LibreCat-ID: 46578 |
Multiobjective Optimization of Non-Smooth PDE-Constrained Problems
M. Bernreuther, M. Dellnitz, B. Gebken, G. Müller, S. Peitz, K. Sonntag, S. Volkwein, ArXiv:2308.01113 (2023).
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| arXiv
M. Bernreuther, M. Dellnitz, B. Gebken, G. Müller, S. Peitz, K. Sonntag, S. Volkwein, ArXiv:2308.01113 (2023).
2022 | Book Chapter | LibreCat-ID: 16296 |
ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation
S. Banholzer, B. Gebken, M. Dellnitz, S. Peitz, S. Volkwein, in: H. Michael, H. Roland, K. Christian, U. Michael, U. Stefan (Eds.), Non-Smooth and Complementarity-Based Distributed Parameter Systems, Springer, Cham, 2022, pp. 43–76.
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S. Banholzer, B. Gebken, M. Dellnitz, S. Peitz, S. Volkwein, in: H. Michael, H. Roland, K. Christian, U. Michael, U. Stefan (Eds.), Non-Smooth and Complementarity-Based Distributed Parameter Systems, Springer, Cham, 2022, pp. 43–76.
2022 | Book Chapter | LibreCat-ID: 30294
Efficient Virtual Design and Testing of Autonomous Vehicles
S. Peitz, M. Dellnitz, S. Bannenberg, in: H.G. Bock, K.-H. Küfer, P. Maas, A. Milde, V. Schulz (Eds.), German Success Stories in Industrial Mathematics, Springer International Publishing, Cham, 2022.
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S. Peitz, M. Dellnitz, S. Bannenberg, in: H.G. Bock, K.-H. Küfer, P. Maas, A. Milde, V. Schulz (Eds.), German Success Stories in Industrial Mathematics, Springer International Publishing, Cham, 2022.
2022 | Journal Article | LibreCat-ID: 29673 |
Koopman analysis of quantum systems
S. Klus, F. Nüske, S. Peitz, Journal of Physics A: Mathematical and Theoretical 55 (2022) 314002.
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S. Klus, F. Nüske, S. Peitz, Journal of Physics A: Mathematical and Theoretical 55 (2022) 314002.
2022 | Preprint | LibreCat-ID: 33150 |
Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients
M.B. Berkemeier, S. Peitz, ArXiv:2208.12094 (2022).
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M.B. Berkemeier, S. Peitz, ArXiv:2208.12094 (2022).
2022 | Journal Article | LibreCat-ID: 20731 |
On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation
K. Bieker, B. Gebken, S. Peitz, IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (2022) 7797–7808.
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K. Bieker, B. Gebken, S. Peitz, IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (2022) 7797–7808.
2022 | Book Chapter | LibreCat-ID: 29727
Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction
M.C. Wohlleben, A. Bender, S. Peitz, W. Sextro, in: Machine Learning, Optimization, and Data Science, Springer International Publishing, Cham, 2022.
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M.C. Wohlleben, A. Bender, S. Peitz, W. Sextro, in: Machine Learning, Optimization, and Data Science, Springer International Publishing, Cham, 2022.
2021 | Journal Article | LibreCat-ID: 21337 |
Derivative-Free Multiobjective Trust Region Descent Method Using Radial Basis Function Surrogate Models
M.B. Berkemeier, S. Peitz, Mathematical and Computational Applications 26 (2021).
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M.B. Berkemeier, S. Peitz, Mathematical and Computational Applications 26 (2021).
2021 | Journal Article | LibreCat-ID: 16867 |
An efficient descent method for locally Lipschitz multiobjective optimization problems
B. Gebken, S. Peitz, Journal of Optimization Theory and Applications 188 (2021) 696–723.
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B. Gebken, S. Peitz, Journal of Optimization Theory and Applications 188 (2021) 696–723.
2021 | Journal Article | LibreCat-ID: 16295 |
Inverse multiobjective optimization: Inferring decision criteria from data
B. Gebken, S. Peitz, Journal of Global Optimization 80 (2021) 3–29.
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B. Gebken, S. Peitz, Journal of Global Optimization 80 (2021) 3–29.
2021 | Journal Article | LibreCat-ID: 16294 |
Explicit multiobjective model predictive control for nonlinear systems with symmetries
S. Ober-Blöbaum, S. Peitz, International Journal of Robust and Nonlinear Control 31(2) (2021) 380–403.
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S. Ober-Blöbaum, S. Peitz, International Journal of Robust and Nonlinear Control 31(2) (2021) 380–403.
2020 | Book Chapter | LibreCat-ID: 17411
Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach
K. Flaßkamp, S. Ober-Blöbaum, S. Peitz, in: O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum, K. Padberg-Gehle (Eds.), Advances in Dynamics, Optimization and Computation, Springer, Cham, 2020.
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K. Flaßkamp, S. Ober-Blöbaum, S. Peitz, in: O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum, K. Padberg-Gehle (Eds.), Advances in Dynamics, Optimization and Computation, Springer, Cham, 2020.
2020 | Journal Article | LibreCat-ID: 10596
Pareto Explorer: a global/local exploration tool for many-objective optimization problems
O. Schütze, O. Cuate, A. Martín, S. Peitz, M. Dellnitz, Engineering Optimization 52 (2020) 832–855.
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O. Schütze, O. Cuate, A. Martín, S. Peitz, M. Dellnitz, Engineering Optimization 52 (2020) 832–855.
2020 | Journal Article | LibreCat-ID: 16288
Data-driven approximation of the Koopman generator: Model reduction, system identification, and control
S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, C. Schütte, Physica D: Nonlinear Phenomena 406 (2020).
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S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, C. Schütte, Physica D: Nonlinear Phenomena 406 (2020).
2020 | Book Chapter | LibreCat-ID: 16289
Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator
S. Peitz, S. Klus, in: Lecture Notes in Control and Information Sciences, Springer, Cham, 2020, pp. 257–282.
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S. Peitz, S. Klus, in: Lecture Notes in Control and Information Sciences, Springer, Cham, 2020, pp. 257–282.
2020 | Journal Article | LibreCat-ID: 16290 |
Deep model predictive flow control with limited sensor data and online learning
K. Bieker, S. Peitz, S.L. Brunton, J.N. Kutz, M. Dellnitz, Theoretical and Computational Fluid Dynamics 34 (2020) 577–591.
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K. Bieker, S. Peitz, S.L. Brunton, J.N. Kutz, M. Dellnitz, Theoretical and Computational Fluid Dynamics 34 (2020) 577–591.
2020 | Journal Article | LibreCat-ID: 16309
Data-Driven Model Predictive Control using Interpolated Koopman Generators
S. Peitz, S.E. Otto, C.W. Rowley, SIAM Journal on Applied Dynamical Systems 19 (2020) 2162–2193.
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S. Peitz, S.E. Otto, C.W. Rowley, SIAM Journal on Applied Dynamical Systems 19 (2020) 2162–2193.