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 .