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66 Publications
2024 | Preprint | LibreCat-ID: 51160 | 
Philipp, F. M., Schaller, M., Boshoff, S., Peitz, S., Nüske, F., & Worthmann, K. (2024). Extended Dynamic Mode Decomposition: Sharp bounds on the sample efficiency. In arXiv:2402.02494.
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| arXiv
2024 | Journal Article | LibreCat-ID: 46019 |
Sonntag, K., & Peitz, S. (2024). Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems. Journal of Optimization Theory and Applications. https://doi.org/10.1007/s10957-024-02389-3
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2024 | Preprint | LibreCat-ID: 51334 |
Sonntag, K., Gebken, B., Müller, G., Peitz, S., & Volkwein, S. (2024). A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces. In arXiv:2402.06376.
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| arXiv
2024 | Journal Article | LibreCat-ID: 40171 |
Peitz, S., Stenner, J., Chidananda, V., Wallscheid, O., Brunton, S. L., & Taira, K. (2024). Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning. Physica D: Nonlinear Phenomena, 461, 134096. https://doi.org/10.1016/j.physd.2024.134096
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2024 | Journal Article | LibreCat-ID: 33461 |
Otto, S. E., Peitz, S., & Rowley, C. W. (2024). Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories. SIAM Journal on Applied Dynamical Systems, 23(1), 885–923. https://doi.org/10.1137/22M1523601
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| arXiv
2024 | Journal Article | LibreCat-ID: 38031 |
Philipp, F., Schaller, M., Worthmann, K., Peitz, S., & Nüske, F. (2024). Error bounds for kernel-based approximations of the Koopman operator. Applied and Computational Harmonic Analysis , 71, Article 101657. https://doi.org/10.1016/j.acha.2024.101657
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| arXiv
2024 | Preprint | LibreCat-ID: 53793 |
Harder, H., & Peitz, S. (n.d.). Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines.
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2024 | Preprint | LibreCat-ID: 52758
Harder, H., & Peitz, S. (2024). On the continuity and smoothness of the value function in reinforcement learning and optimal control.
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2024 | Preprint | LibreCat-ID: 53858 |
Akhter, J., Fährmann, P. D., Sonntag, K., & Peitz, S. (2024). Common pitfalls to avoid while using multiobjective optimization in machine learning. In arXiv.
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2024 | Journal Article | LibreCat-ID: 32447
Sonntag, K., & Peitz, S. (2024). Fast Convergence of Inertial Multiobjective Gradient-Like Systems with Asymptotic Vanishing Damping. SIAM Journal on Optimization, 34(3), 2259–2286. https://doi.org/10.1137/23M1588512
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2024 | Conference Paper | LibreCat-ID: 46649 |
Hotegni, S. S., Berkemeier, M. B., & Peitz, S. (2024). Multi-Objective Optimization for Sparse Deep Multi-Task Learning. 2024 International Joint Conference on Neural Networks (IJCNN), 9. https://doi.org/10.1109/IJCNN60899.2024.10650994
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2023 | Journal Article | LibreCat-ID: 21199 |
Peitz, S., & Bieker, K. (2023). On the Universal Transformation of Data-Driven Models to Control Systems. Automatica, 149, Article 110840. https://doi.org/10.1016/j.automatica.2022.110840
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2023 | Preprint | LibreCat-ID: 48502 |
Peitz, S., Hunstig, A., Rose, H., & Meier, T. (2023). Accelerating the analysis of optical quantum systems using the Koopman operator.
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2023 | Preprint | LibreCat-ID: 51159 |
Amakor, A. C., Sonntag, K., & Peitz, S. (2023). A multiobjective continuation method to compute the regularization path of deep neural networks. In arXiv.
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2023 | Preprint | LibreCat-ID: 51158 |
Philipp, F., Schaller, M., Worthmann, K., Peitz, S., & Nüske, F. (2023). Error analysis of kernel EDMD for prediction and control in the Koopman framework. In arXiv:2312.10460.
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| arXiv
2023 | Preprint | LibreCat-ID: 46578 |
Bernreuther, M., Dellnitz, M., Gebken, B., Müller, G., Peitz, S., Sonntag, K., & Volkwein, S. (2023). Multiobjective Optimization of Non-Smooth PDE-Constrained Problems. In arXiv:2308.01113.
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| arXiv
2023 | Conference Paper | LibreCat-ID: 54838
Boshoff, S., Stenner, J., Weber, D., Meyer, M., Chidananda, V., Peitz, S., & Wallscheid, O. (2023). Hybrid control of interconnected power converters using both expert-driven droop and data-driven reinforcement learning approaches. IEEE Power and Energy Student Summit (PESS), 124–129.
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2023 | Conference Paper | LibreCat-ID: 54839
Meyer, M., Weber, D., Chidananda, V., Schweins, O., Stenner, J., Boshoff, S., Peitz, S., & Wallscheid, O. (2023). ElectricGrid.jl – Automated modeling of decentralized electrical energy grids. IEEE Power and Energy Student Summit (PESS), 112–117.
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2023 | Preprint | LibreCat-ID: 42160 |
Werner, S., & Peitz, S. (2023). Learning a model is paramount for sample efficiency in reinforcement learning control of PDEs. In arXiv:2302.07160.
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| arXiv
2023 | Journal Article | LibreCat-ID: 27426 |
Gebken, B., Bieker, K., & Peitz, S. (2023). On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization, 85(3), 709–741. https://doi.org/10.1007/s10898-022-01223-2
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