Philipp, Friedrich M., Manuel Schaller, Septimus Boshoff, Sebastian Peitz, Feliks Nüske, and Karl Worthmann. “Extended Dynamic Mode Decomposition: Sharp Bounds on the Sample  Efficiency.” ArXiv:2402.02494, 2024.

Sonntag, Konstantin, and Sebastian Peitz. “Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems.”https://doi.org/10.1007/s10957-024-02389-3__Journal of Optimization Theory and Applications, 2024.https://doi.org/10.1007/s10957-024-02389-3 .

Sonntag, Konstantin, Bennet Gebken, Georg Müller, Sebastian Peitz, and Stefan Volkwein. “A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces.” ArXiv:2402.06376, 2024.

Peitz, Sebastian, Jan Stenner, Vikas Chidananda, Oliver Wallscheid, Steven L. Brunton, and Kunihiko Taira. “Distributed Control of Partial Differential Equations Using  Convolutional Reinforcement Learning.”https://doi.org/10.1016/j.physd.2024.134096__Physica D: Nonlinear Phenomena 461 (2024): 134096.https://doi.org/10.1016/j.physd.2024.134096 .

Otto, Samuel E., Sebastian Peitz, and Clarence W. Rowley. “Learning Bilinear Models of Actuated Koopman Generators from  Partially-Observed Trajectories.”https://doi.org/10.1137/22M1523601__SIAM Journal on Applied Dynamical Systems 23, no. 1 (2024): 885–923.https://doi.org/10.1137/22M1523601 .

Philipp, Friedrich, Manuel Schaller, Karl Worthmann, Sebastian Peitz, and Feliks Nüske. “Error Bounds for Kernel-Based Approximations of the Koopman Operator.”https://doi.org/10.1016/j.acha.2024.101657__Applied and Computational Harmonic Analysis  71 (2024).https://doi.org/10.1016/j.acha.2024.101657 .

Akhter, Junaid, Paul David Fährmann, Konstantin Sonntag, and Sebastian Peitz. “Common Pitfalls to Avoid While Using Multiobjective Optimization in Machine Learning.” ArXiv, 2024.

Peitz, Sebastian, and Katharina Bieker. “On the Universal Transformation of Data-Driven Models to Control Systems.”https://doi.org/10.1016/j.automatica.2022.110840__Automatica 149 (2023).https://doi.org/10.1016/j.automatica.2022.110840 .

Werner, Stefan, and Sebastian Peitz. “Learning a Model Is Paramount for Sample Efficiency in Reinforcement  Learning Control of PDEs.” ArXiv:2302.07160, 2023.

Gebken, Bennet, Katharina Bieker, and Sebastian Peitz. “On the Structure of Regularization Paths for Piecewise Differentiable Regularization Terms.”https://doi.org/10.1007/s10898-022-01223-2__Journal of Global Optimization 85, no. 3 (2023): 709–41.https://doi.org/10.1007/s10898-022-01223-2 .

Schaller, Manuel, Karl Worthmann, Friedrich Philipp, Sebastian Peitz, and Feliks Nüske. “Towards Reliable Data-Based Optimal and Predictive Control Using Extended DMD.”https://doi.org/10.1016/j.ifacol.2023.02.029__In IFAC-PapersOnLine, 56:169–74, 2023.https://doi.org/10.1016/j.ifacol.2023.02.029 .

Hotegni, Sedjro Salomon, Sepideh Mahabadi, and Ali Vakilian. “Approximation Algorithms for Fair Range Clustering.” In Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023., n.d.

Peitz, Sebastian, Hans Harder, Feliks Nüske, Friedrich Philipp, Manuel Schaller, and Karl Worthmann. “Partial Observations, Coarse Graining and Equivariance in Koopman  Operator Theory for Large-Scale Dynamical Systems.” ArXiv:2307.15325, 2023.

Nüske, Feliks, Sebastian Peitz, Friedrich Philipp, Manuel Schaller, and Karl Worthmann. “Finite-Data Error Bounds for Koopman-Based Prediction and Control.”https://doi.org/10.1007/s00332-022-09862-1__Journal of Nonlinear Science 33 (2023).https://doi.org/10.1007/s00332-022-09862-1 .

Hotegni, Sedjro Salomon, Sebastian Peitz, and Manuel Bastian Berkemeier. “Multi-Objective Optimization for Sparse Deep Neural Network Training.” ArXiv:2308.12243, 2023.

Dellnitz, Michael, Eyke Hüllermeier, Marvin Lücke, Sina Ober-Blöbaum, Christian Offen, Sebastian Peitz, and Karlson Pfannschmidt. “Efficient Time Stepping for Numerical Integration Using Reinforcement  Learning.”https://doi.org/10.1137/21M1412682__SIAM Journal on Scientific Computing 45, no. 2 (2023): 9–95.https://doi.org/10.1137/21M1412682 .

Wallscheid, Oliver, Sebastian Peitz, Jan Stenner, Daniel Weber, Septimus Boshoff, Marvin Meyer, Vikas Chidananda, and Oliver Schweins. “ElectricGrid.Jl - A Julia-Based Modeling and Simulationtool for Power Electronics-Driven Electric Energy Grids.”https://doi.org/10.21105/joss.05616__Journal of Open Source Software 8, no. 89 (2023).https://doi.org/10.21105/joss.05616 .

Wohlleben, Meike Claudia, Lars Muth, Sebastian Peitz, and Walter Sextro. “Transferability of a Discrepancy Model for the Dynamics of Electromagnetic Oscillating Circuits.”https://doi.org/10.1002/pamm.202300039__In Proceedings in Applied Mathematics and Mechanics. Wiley, 2023.https://doi.org/10.1002/pamm.202300039 .

Peitz, Sebastian, Anna Hunstig, Hendrik Rose, and Torsten Meier. “Accelerating the Analysis of Optical Quantum Systems Using the Koopman Operator,” 2023.

Amakor, Augustina Chidinma, Konstantin Sonntag, and Sebastian Peitz. “A Multiobjective Continuation Method to Compute the Regularization Path of Deep Neural Networks.” ArXiv, 2023.