Sebastian Peitz

54 papers A 1B 1Journal 46Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Automatic feature identification in least-squares policy iteration using the Koopman operator framework. CoRR Christian Mugisho Zagabe, Sebastian Peitz
2026	J	`jnl`	Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh-bénard convection. Neurocomputing Thorben Markmann, Michiel Straat, Sebastian Peitz, Barbara Hammer
2026	J	`jnl`	Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection. CoRR Tim Plotzki, Sebastian Peitz
2026	J	`jnl`	Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control. CoRR Jannis Becktepe, Aleksandra Franz, Nils Thuerey, Sebastian Peitz
2025	J	`jnl`	Bayesian Transfer Operators in Reproducing Kernel Hilbert Spaces. CoRR Septimus Boshoff, Sebastian Peitz, Stefan Klus
2025	J	`jnl`	Control of Rayleigh-Bénard Convection: Effectiveness of Reinforcement Learning in the Turbulent Regime. CoRR Thorben Markmann, Michiel Straat, Sebastian Peitz, Barbara Hammer
2025	A	`conf`	Effective Backdoor Learning on Open-Set Face Recognition Systems. WACV Diana Voth, Leonidas Dane, Jonas Grebe, Sebastian Peitz, Philipp Terhörst
2025	J	`jnl`	Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems. CoRR Hans Harder, Abhijeet Vishwasrao, Luca Guastoni, Ricardo Vinuesa, Sebastian Peitz
2025	—	`conf`	Enhancing Adversarial Robustness Through Multi-objective Representation Learning. ICANN (1) Sèdjro Salomon Hotegni, Sebastian Peitz
2025	J	`jnl`	Error Analysis of Kernel EDMD for Prediction and Control in the Koopman Framework. J. Nonlinear Sci. Friedrich M. Philipp, Manuel Schaller, Karl Worthmann, Sebastian Peitz, Feliks Nüske
2025	J	`jnl`	Improving the Robustness of Control of Chaotic Convective Flows with Domain-Informed Reinforcement Learning. CoRR Michiel Straat, Thorben Markmann, Sebastian Peitz, Barbara Hammer
2025	J	`jnl`	Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. Open J. Math. Optim. Manuel Berkemeier, Sebastian Peitz
2025	J	`jnl`	SPREAD: Sampling-based Pareto front Refinement via Efficient Adaptive Diffusion. CoRR Sèdjro Salomon Hotegni, Sebastian Peitz
2025	J	`jnl`	Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders. CoRR Fynn Fromme, Christine Allen-Blanchette, Hans Harder, Sebastian Peitz
2025	—	`conf`	Surrogate-Assisted Multi-objective Design of Complex Multibody Systems. ICANN (4) Augustina C. Amakor, Manuel Berkemeier, Meike Wohlleben, Walter Sextro, Sebastian Peitz
2024	J	`jnl`	A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces. J. Optim. Theory Appl. Konstantin Sonntag, Bennet Gebken, Georg Müller, Sebastian Peitz, Stefan Volkwein
2024	—	`conf`	Accelerating the analysis of optical quantum systems using the Koopman operator. CDC Anna Hunstig, Sebastian Peitz, Hendrik Rose, Torsten Meier
2024	J	`jnl`	Common pitfalls to avoid while using multiobjective optimization in machine learning. CoRR Junaid Akhter, Paul David Fährmann, Konstantin Sonntag, Sebastian Peitz
2024	J	`jnl`	Fast Convergence of Inertial Multiobjective Gradient-Like Systems with Asymptotic Vanishing Damping. SIAM J. Optim. Konstantin Sonntag, Sebastian Peitz
2024	J	`jnl`	Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems. J. Optim. Theory Appl. Konstantin Sonntag, Sebastian Peitz
2024	J	`jnl`	Learning Bilinear Models of Actuated Koopman Generators from Partially Observed Trajectories. SIAM J. Appl. Dyn. Syst. Samuel E. Otto, Sebastian Peitz, Clarence W. Rowley
2024	J	`jnl`	MOREL: Enhancing Adversarial Robustness through Multi-Objective Representation Learning. CoRR Sèdjro Salomon Hotegni, Sebastian Peitz
2024	B	`conf`	Multi-Objective Optimization for Sparse Deep Multi-Task Learning. IJCNN Sèdjro Salomon Hotegni, Manuel Berkemeier, Sebastian Peitz
2024	J	`jnl`	Multi-objective Deep Learning: Taxonomy and Survey of the State of the Art. CoRR Sebastian Peitz, Sèdjro Salomon Hotegni
2024	—	`conf`	Numerical Evidence for Sample Efficiency of Model-Based Over Model-Free Reinforcement Learning Control of Partial Differential Equations. ECC Stefan Werner, Sebastian Peitz
2024	—	`conf`	On the continuity and smoothness of the value function in reinforcement learning and optimal control. CDC Hans Harder, Sebastian Peitz
2024	J	`jnl`	On the continuity and smoothness of the value function in reinforcement learning and optimal control. CoRR Hans Harder, Sebastian Peitz
2024	J	`jnl`	Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines. CoRR Hans Harder, Sebastian Peitz
2024	J	`jnl`	Surrogate-assisted multi-objective design of complex multibody systems. CoRR Augustina C. Amakor, Manuel Berkemeier, Meike Wohlleben, Walter Sextro, Sebastian Peitz
2024	J	`jnl`	The impact of AI on engineering design procedures for dynamical systems. CoRR Kristin Miriam de Payrebrune, Kathrin Flaßkamp, Tom Ströhla, Thomas Sattel, Dieter Bestle, Benedict Röder, Peter Eberhard, Sebastian Peitz, Marcus Stoffel, Rutwik Gulakala, Aditya Borse, Meike Wohlleben, Walter Sextro, Maximilian Raff, C. David Remy, Manish Yadav, Merten Stender, Jan van Delden, Timo Lüddecke, Sabine C. Langer, Julius Schultz, Christopher Blech
2023	J	`jnl`	A multiobjective continuation method to compute the regularization path of deep neural networks. CoRR Augustina C. Amakor, Konstantin Sonntag, Sebastian Peitz
2023	J	`jnl`	Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning. CoRR Sebastian Peitz, Jan Stenner, Vikas Chidananda, Oliver Wallscheid, Steven L. Brunton, Kunihiko Taira
2023	J	`jnl`	Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning. SIAM J. Sci. Comput. Michael Dellnitz, Eyke Hüllermeier, Marvin Lücke, Sina Ober-Blöbaum, Christian Offen, Sebastian Peitz, Karlson Pfannschmidt
2023	J	`jnl`	ElectricGrid.jl - A Julia-based modeling and simulation tool for power electronics-driven electric energy grids. J. Open Source Softw. Oliver Wallscheid, Sebastian Peitz, Jan Stenner, Daniel Weber, Septimus Boshoff, Marvin Meyer, Vikas Chidananda, Oliver Schweins
2023	J	`jnl`	Finite-Data Error Bounds for Koopman-Based Prediction and Control. J. Nonlinear Sci. Feliks Nüske, Sebastian Peitz, Friedrich Philipp, Manuel Schaller, Karl Worthmann
2023	J	`jnl`	Learning a model is paramount for sample efficiency in reinforcement learning control of PDEs. CoRR Stefan Werner, Sebastian Peitz
2023	J	`jnl`	Multi-Objective Optimization for Sparse Deep Neural Network Training. CoRR Sèdjro S. Hotegni, Sebastian Peitz, Manuel Berkemeier
2023	J	`jnl`	On the structure of regularization paths for piecewise differentiable regularization terms. J. Glob. Optim. Bennet Gebken, Katharina Bieker, Sebastian Peitz
2023	J	`jnl`	On the universal transformation of data-driven models to control systems. Autom. Sebastian Peitz, Katharina Bieker
2023	J	`jnl`	Partial observations, coarse graining and equivariance in Koopman operator theory for large-scale dynamical systems. CoRR Sebastian Peitz, Hans Harder, Feliks Nüske, Friedrich Philipp, Manuel Schaller, Karl Worthmann
2022	J	`jnl`	Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories. CoRR Samuel E. Otto, Sebastian Peitz, Clarence W. Rowley
2022	J	`jnl`	On the Treatment of Optimization Problems With L1 Penalty Terms via Multiobjective Continuation. IEEE Trans. Pattern Anal. Mach. Intell. Katharina Bieker, Bennet Gebken, Sebastian Peitz
2021	J	`jnl`	An Efficient Descent Method for Locally Lipschitz Multiobjective Optimization Problems. J. Optim. Theory Appl. Bennet Gebken, Sebastian Peitz
2021	J	`jnl`	Derivative-Free Multiobjective Trust Region Descent MethodUsing Radial Basis Function Surrogate Models. CoRR Manuel Berkemeier, Sebastian Peitz
2021	—	`conf`	Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction. LOD Meike Wohlleben, Amelie Bender, Sebastian Peitz, Walter Sextro
2021	J	`jnl`	Efficient time stepping for numerical integration using reinforcement learning. CoRR Michael Dellnitz, Eyke Hüllermeier, Marvin Lücke, Sina Ober-Blöbaum, Christian Offen, Sebastian Peitz, Karlson Pfannschmidt
2021	J	`jnl`	Inverse multiobjective optimization: Inferring decision criteria from data. J. Glob. Optim. Bennet Gebken, Sebastian Peitz
2021	J	`jnl`	On the Universal Transformation of Data-Driven Models to Control Systems. CoRR Sebastian Peitz, Katharina Bieker
2020	J	`jnl`	Data-Driven Model Predictive Control using Interpolated Koopman Generators. SIAM J. Appl. Dyn. Syst. Sebastian Peitz, Samuel E. Otto, Clarence W. Rowley
2020	J	`jnl`	On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation. CoRR Katharina Bieker, Bennet Gebken, Sebastian Peitz
2019	J	`jnl`	Deep Model Predictive Control with Online Learning for Complex Physical Systems. CoRR Katharina Bieker, Sebastian Peitz, Steven L. Brunton, J. Nathan Kutz, Michael Dellnitz
2019	J	`jnl`	Koopman operator-based model reduction for switched-system control of PDEs. Autom. Sebastian Peitz, Stefan Klus
2019	J	`jnl`	On the hierarchical structure of Pareto critical sets. J. Glob. Optim. Bennet Gebken, Sebastian Peitz, Michael Dellnitz
2018	J	`jnl`	Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions. CoRR Stefan Klus, Sebastian Peitz, Ingmar Schuster