Sebastian Peitz

Sebastian Peitz

sebastian.peitz@upb.de
Institution: Paderborn University
Department: Department of Computer Science
Position: Data Science for Engineering
http://www.cs.upb.de/dse

Data-driven model reduction, optimization and control of complex dynamical systems; Reinforcement learning; Multiobjective optimization / Multicriteria machine learning

  • Variance representations and convergence rates for data-driven approximations of Koopman operators (2026)

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    Published at: Physica D Nonlinear Phenomena (Volume: 492)
    DOI: 10.1016/j.physd.2026.135223

  • Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh–bénard convection (2026)

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    Published at: Neurocomputing (Volume: 679)
    DOI: 10.1016/j.neucom.2026.133201

  • Enhancing Adversarial Robustness Through Multi-objective Representation Learning (2026)

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    Published at: Lecture Notes in Computer Science (Volume: 16068 LNCS)
    DOI: 10.1007/978-3-032-04558-4_35

  • Common Pitfalls to Avoid While Using Multiobjective Optimization in Machine Learning (2026)

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    Published at: SIAM Review (Volume: 68)
    DOI: 10.1137/24M1658875

  • Surrogate-Assisted Multi-objective Design of Complex Multibody Systems (2026)

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    Published at: Lecture Notes in Computer Science (Volume: 16071 LNCS)
    DOI: 10.1007/978-3-032-04555-3_21

  • Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems (2026)

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    Published at: Proceedings of Machine Learning Research (Volume: 331)

  • Evaluating physics-based, hybrid, and data-driven models for rubber-metal bushings: Balancing accuracy, implementation complexity, and efficiency (2026)

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    Published at: Multibody System Dynamics
    DOI: 10.1007/s11044-026-10146-9

  • Error Analysis of Kernel EDMD for Prediction and Control in the Koopman Framework (2025)

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    Published at: Journal of Nonlinear Science (Volume: 35)
    DOI: 10.1007/s00332-025-10182-3

  • Group-convolutional extended dynamic mode decomposition (2025)

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    Published at: Physica D Nonlinear Phenomena (Volume: 480)
    DOI: 10.1016/j.physd.2025.134725

  • Multi-objective deep learning: Taxonomy and survey of the state of the art (2025)

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    Published at: Machine Learning with Applications (Volume: 21)
    DOI: 10.1016/j.mlwa.2025.100700