Extended Dynamic Mode Decomposition: Sharp bounds on the sample  efficiency
F.M. Philipp, M. Schaller, S. Boshoff, S. Peitz, F. Nüske, K. Worthmann, ArXiv:2402.02494 (2024).
LibreCat: /record/51160
arXiv: 2402.02494

Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems
K. Sonntag, S. Peitz, Journal of Optimization Theory and Applications (2024).
LibreCat: /record/46019
DOI: 10.1007/s10957-024-02389-3

A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces
K. Sonntag, B. Gebken, G. Müller, S. Peitz, S. Volkwein, ArXiv:2402.06376 (2024).
LibreCat: /record/51334
arXiv: 	2402.06376

Distributed Control of Partial Differential Equations Using  Convolutional Reinforcement Learning
S. Peitz, J. Stenner, V. Chidananda, O. Wallscheid, S.L. Brunton, K. Taira, Physica D: Nonlinear Phenomena 461 (2024) 134096.
LibreCat: /record/40171
DOI: 10.1016/j.physd.2024.134096

Learning Bilinear Models of Actuated Koopman Generators from  Partially-Observed Trajectories
S.E. Otto, S. Peitz, C.W. Rowley, SIAM Journal on Applied Dynamical Systems 23 (2024) 885–923.
LibreCat: /record/33461
DOI: 10.1137/22M1523601
arXiv: 2209.09977

Error bounds for kernel-based approximations of the Koopman operator
F. Philipp, M. Schaller, K. Worthmann, S. Peitz, F. Nüske, Applied and Computational Harmonic Analysis  71 (2024).
LibreCat: /record/38031
DOI: 10.1016/j.acha.2024.101657
arXiv: 2301.08637

Common pitfalls to avoid while using multiobjective optimization in machine learning
J. Akhter, P.D. Fährmann, K. Sonntag, S. Peitz, ArXiv (2024).
LibreCat: /record/53858

On the Universal Transformation of Data-Driven Models to Control Systems
S. Peitz, K. Bieker, Automatica 149 (2023).
LibreCat: /record/21199
DOI: 10.1016/j.automatica.2022.110840

Learning a model is paramount for sample efficiency in reinforcement  learning control of PDEs
S. Werner, S. Peitz, ArXiv:2302.07160 (2023).
LibreCat: /record/42160
arXiv: 2302.07160

On the structure of regularization paths for piecewise differentiable regularization terms
B. Gebken, K. Bieker, S. Peitz, Journal of Global Optimization 85 (2023) 709–741.
LibreCat: /record/27426
DOI: 10.1007/s10898-022-01223-2

Towards reliable data-based optimal and predictive control using extended DMD
M. Schaller, K. Worthmann, F. Philipp, S. Peitz, F. Nüske, in: IFAC-PapersOnLine, 2023, pp. 169–174.
LibreCat: /record/30125
DOI: 10.1016/j.ifacol.2023.02.029
arXiv: 2202.09084

Approximation Algorithms for Fair Range Clustering
S.S. Hotegni, S. Mahabadi, A. Vakilian, in: Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023., n.d.
LibreCat: /record/45695

Partial observations, coarse graining and equivariance in Koopman  operator theory for large-scale dynamical systems
S. Peitz, H. Harder, F. Nüske, F. Philipp, M. Schaller, K. Worthmann, ArXiv:2307.15325 (2023).
LibreCat: /record/46579
arXiv: 2307.15325

Finite-data error bounds for Koopman-based prediction and control
F. Nüske, S. Peitz, F. Philipp, M. Schaller, K. Worthmann, Journal of Nonlinear Science 33 (2023).
LibreCat: /record/23428
DOI: 10.1007/s00332-022-09862-1

Multi-Objective Optimization for Sparse Deep Neural Network Training
S.S. Hotegni, S. Peitz, M.B. Berkemeier, ArXiv:2308.12243 (2023).
LibreCat: /record/46649
arXiv: 2308.12243

Efficient time stepping for numerical integration using reinforcement  learning
M. Dellnitz, E. Hüllermeier, M. Lücke, S. Ober-Blöbaum, C. Offen, S. Peitz, K. Pfannschmidt, SIAM Journal on Scientific Computing 45 (2023) 9–5.
LibreCat: /record/21600
DOI: 10.1137/21M1412682
arXiv: arXiv:2104.03562

ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids
O. Wallscheid, S. Peitz, J. Stenner, D. Weber, S. Boshoff, M. Meyer, V. Chidananda, O. Schweins, Journal of Open Source Software 8 (2023).
LibreCat: /record/46784
DOI: 10.21105/joss.05616

Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits
M.C. Wohlleben, L. Muth, S. Peitz, W. Sextro, in: Proceedings in Applied Mathematics and Mechanics, Wiley, 2023.
LibreCat: /record/46813
DOI: 10.1002/pamm.202300039

Accelerating the analysis of optical quantum systems using the Koopman operator
S. Peitz, A. Hunstig, H. Rose, T. Meier, (2023).
LibreCat: /record/48502

A multiobjective continuation method to compute the regularization path of deep neural networks
A.C. Amakor, K. Sonntag, S. Peitz, ArXiv (2023).
LibreCat: /record/51159