F. M. Philipp, M. Schaller, S. Boshoff, S. Peitz, F. Nüske, and K. Worthmann, “Extended Dynamic Mode Decomposition: Sharp bounds on the sample  efficiency,” arXiv:2402.02494. 2024.

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

K. Sonntag, B. Gebken, G. Müller, S. Peitz, and S. Volkwein, “A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces,” arXiv:2402.06376. 2024.

S. Peitz, J. Stenner, V. Chidananda, O. Wallscheid, S. L. Brunton, and K. Taira, “Distributed Control of Partial Differential Equations Using  Convolutional Reinforcement Learning,”10.1016/j.physd.2024.134096__Physica D: Nonlinear Phenomena, vol. 461, p. 134096, 2024, doi:10.1016/j.physd.2024.134096 .

S. E. Otto, S. Peitz, and C. W. Rowley, “Learning Bilinear Models of Actuated Koopman Generators from  Partially-Observed Trajectories,”10.1137/22M1523601__SIAM Journal on Applied Dynamical Systems, vol. 23, no. 1, pp. 885–923, 2024, doi:10.1137/22M1523601 .

F. Philipp, M. Schaller, K. Worthmann, S. Peitz, and F. Nüske, “Error bounds for kernel-based approximations of the Koopman operator,”10.1016/j.acha.2024.101657__Applied and Computational Harmonic Analysis , vol. 71, Art. no. 101657, 2024, doi:10.1016/j.acha.2024.101657 .

H. Harder and S. Peitz, “Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines.” .

H. Harder and S. Peitz, “On the continuity and smoothness of the value function in reinforcement learning and optimal control.” 2024.

J. Akhter, P. D. Fährmann, K. Sonntag, and S. Peitz, “Common pitfalls to avoid while using multiobjective optimization in machine learning,” arXiv. 2024.

S. Peitz and K. Bieker, “On the Universal Transformation of Data-Driven Models to Control Systems,”10.1016/j.automatica.2022.110840__Automatica, vol. 149, Art. no. 110840, 2023, doi:10.1016/j.automatica.2022.110840 .

S. Werner and S. Peitz, “Learning a model is paramount for sample efficiency in reinforcement  learning control of PDEs,” arXiv:2302.07160. 2023.

B. Gebken, K. Bieker, and S. Peitz, “On the structure of regularization paths for piecewise differentiable regularization terms,”10.1007/s10898-022-01223-2__Journal of Global Optimization, vol. 85, no. 3, pp. 709–741, 2023, doi:10.1007/s10898-022-01223-2 .

M. Schaller, K. Worthmann, F. Philipp, S. Peitz, and F. Nüske, “Towards reliable data-based optimal and predictive control using extended DMD,”10.1016/j.ifacol.2023.02.029__in IFAC-PapersOnLine, 2023, vol. 56, no. 1, pp. 169–174, doi:10.1016/j.ifacol.2023.02.029 .

S. Peitz, H. Harder, F. Nüske, F. Philipp, M. Schaller, and K. Worthmann, “Partial observations, coarse graining and equivariance in Koopman  operator theory for large-scale dynamical systems,” arXiv:2307.15325. 2023.

F. Nüske, S. Peitz, F. Philipp, M. Schaller, and K. Worthmann, “Finite-data error bounds for Koopman-based prediction and control,”10.1007/s00332-022-09862-1__Journal of Nonlinear Science, vol. 33, Art. no. 14, 2023, doi:10.1007/s00332-022-09862-1 .

S. S. Hotegni, S. Peitz, and M. B. Berkemeier, “Multi-Objective Optimization for Sparse Deep Neural Network Training,” arXiv:2308.12243. 2023.

M. Dellnitz et al., “Efficient time stepping for numerical integration using reinforcement  learning,”10.1137/21M1412682__SIAM Journal on Scientific Computing, vol. 45, no. 2, pp. 9–5, 2023, doi:10.1137/21M1412682 .

O. Wallscheid et al., “ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids,”10.21105/joss.05616__Journal of Open Source Software, vol. 8, no. 89, Art. no. 5616, 2023, doi:10.21105/joss.05616 .

M. C. Wohlleben, L. Muth, S. Peitz, and W. Sextro, “Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits,”10.1002/pamm.202300039__2023, doi:10.1002/pamm.202300039 .

S. Peitz, A. Hunstig, H. Rose, and T. Meier, “Accelerating the analysis of optical quantum systems using the Koopman operator.” 2023.