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277 Publications


2021 | Preprint | LibreCat-ID: 21600
Dellnitz, M., Hüllermeier, E., Lücke, M., Ober-Blöbaum, S., Offen, C., Peitz, S., & Pfannschmidt, K. (2021). Efficient time stepping for numerical integration using reinforcement  learning. ArXiv:2104.03562.
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2021 | Journal Article | LibreCat-ID: 16295
Gebken, B., & Peitz, S. (2021). Inverse multiobjective optimization: Inferring decision criteria from data. Journal of Global Optimization, 80, 3–29. https://doi.org/10.1007/s10898-020-00983-z
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2021 | Preprint | LibreCat-ID: 21199
Peitz, S., & Bieker, K. (2021). On the Universal Transformation of Data-Driven Models to Control Systems. ArXiv:2102.04722.
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2021 | Journal Article | LibreCat-ID: 16867
Gebken, B., & Peitz, S. (2021). An efficient descent method for locally Lipschitz multiobjective optimization problems. Journal of Optimization Theory and Applications, 188, 696–723. https://doi.org/10.1007/s10957-020-01803-w
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2021 | Journal Article | LibreCat-ID: 21195
Goelz, C., Mora, K., Stroehlein, J. K., Haase, F. K., Dellnitz, M., Reinsberger, C., & Vieluf, S. (2021). Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults. Cognitive Neurodynamics. https://doi.org/10.1007/s11571-020-09656-9
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2021 | Journal Article | LibreCat-ID: 16294
Ober-Blöbaum, S., & Peitz, S. (2021). Explicit multiobjective model predictive control for nonlinear systems  with symmetries. International Journal of Robust and Nonlinear Control, 31(2), 380–403. https://doi.org/10.1002/rnc.5281
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2021 | Preprint | LibreCat-ID: 21572
Ridderbusch, S., Offen, C., Ober-Blöbaum, S., & Goulart, P. (n.d.). Learning ODE Models with Qualitative Structure Using Gaussian Processes .
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2021 | Journal Article | LibreCat-ID: 21337
Berkemeier, M. B., & Peitz, S. (2021). Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. Mathematical and Computational Applications, 26(2). https://doi.org/10.3390/mca26020031
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2021 | Journal Article | LibreCat-ID: 21820
Nüske, F., Koltai, P., Boninsegna, L., & Clementi, C. (2021). Spectral Properties of Effective Dynamics from Conditional Expectations. Entropy. https://doi.org/10.3390/e23020134
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2020 | Journal Article | LibreCat-ID: 16961
Liebendörfer, M., Göller, R., Biehler, R., Hochmuth, R., Kortemeyer, J., Ostsieker, L., … Schaper, N. (2020). LimSt – Ein Fragebogen zur Erhebung von Lernstrategien im mathematikhaltigen Studium. Journal für Mathematik-Didaktik. https://doi.org/10.1007/s13138-020-00167-y
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2020 | Journal Article | LibreCat-ID: 16290
Bieker, K., Peitz, S., Brunton, S. L., Kutz, J. N., & Dellnitz, M. (2020). Deep model predictive flow control with limited sensor data and online learning. Theoretical and Computational Fluid Dynamics, 34, 577–591. https://doi.org/10.1007/s00162-020-00520-4
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2020 | Preprint | LibreCat-ID: 19941
McLachlan, R. I., & Offen, C. (n.d.). Backward error analysis for variational discretisations of partial  differential equations. ArXiv:2006.14172.
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2020 | Journal Article | LibreCat-ID: 19939
Kreusser, L. M., McLachlan, R. I., & Offen, C. (2020). Detection of high codimensional bifurcations in variational PDEs. Nonlinearity, 33(5), 2335–2363. https://doi.org/10.1088/1361-6544/ab7293
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2020 | Journal Article | LibreCat-ID: 16288
Klus, S., Nüske, F., Peitz, S., Niemann, J.-H., Clementi, C., & Schütte, C. (2020). Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena, 406. https://doi.org/10.1016/j.physd.2020.132416
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2020 | Journal Article | LibreCat-ID: 21819
Klus, S., Nüske, F., & Hamzi, B. (2020). Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator. Entropy. https://doi.org/10.3390/e22070722
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2020 | Journal Article | LibreCat-ID: 10596
Schütze, O., Cuate, O., Martín, A., Peitz, S., & Dellnitz, M. (2020). Pareto Explorer: a global/local exploration tool for many-objective optimization problems. Engineering Optimization, 52(5), 832–855. https://doi.org/10.1080/0305215x.2019.1617286
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2020 | Book Chapter | LibreCat-ID: 16289
Peitz, S., & Klus, S. (2020). Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator. In Lecture Notes in Control and Information Sciences (Vol. 484, pp. 257–282). Cham: Springer. https://doi.org/10.1007/978-3-030-35713-9_10
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2020 | Book Chapter | LibreCat-ID: 13108
Schumacher, J., & Rezat, S. (2020). Rekonstruktion diagrammatischen Schließens beim Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer Zugänge. In G. Kadunz (Ed.), Zeichen und Sprache im Mathematikunterricht. Springer. https://doi.org/10.1007/978-3-662-61194-4_5
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2020 | Journal Article | LibreCat-ID: 16710
Gerlach, R., Ziessler, A., Eckhardt, B., & Dellnitz, M. (2020). A Set-Oriented Path Following Method for the Approximation of Parameter Dependent Attractors. SIAM Journal on Applied Dynamical Systems, 705–723. https://doi.org/10.1137/19m1247139
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2020 | Journal Article | LibreCat-ID: 16309
Peitz, S., Otto, S. E., & Rowley, C. W. (2020). Data-Driven Model Predictive Control using Interpolated Koopman  Generators. SIAM Journal on Applied Dynamical Systems, 19(3), 2162–2193. https://doi.org/10.1137/20M1325678
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