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82 Publications
2020 | Journal Article | LibreCat-ID: 16288
Klus S, Nüske F, Peitz S, Niemann J-H, Clementi C, Schütte C. Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena. 2020;406. doi:10.1016/j.physd.2020.132416
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| DOI
2020 | Journal Article | LibreCat-ID: 16290
Bieker K, Peitz S, Brunton SL, Kutz JN, Dellnitz M. Deep model predictive flow control with limited sensor data and online learning. Theoretical and Computational Fluid Dynamics. 2020. doi:10.1007/s00162-020-00520-4
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2020 | Book Chapter | LibreCat-ID: 16289
Peitz S, Klus S. 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. Lecture Notes in Control and Information Sciences. Cham: Springer; 2020:257-282. doi:10.1007/978-3-030-35713-9_10
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| DOI
2020 | Preprint | LibreCat-ID: 16309
Peitz S, Otto SE, Rowley CW. Data-Driven Model Predictive Control using Interpolated Koopman Generators. arXiv:200307094. 2020.
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2020 | Journal Article | LibreCat-ID: 10596
Schütze O, Cuate O, Martín A, Peitz S, Dellnitz M. Pareto Explorer: a global/local exploration tool for many-objective optimization problems. Engineering Optimization. 2020;52(5):832-855. doi:10.1080/0305215x.2019.1617286
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| DOI
2020 | Preprint | LibreCat-ID: 16297
Hernández Castellanos CI, Ober-Blöbaum S, Peitz S. Explicit Multi-objective Model Predictive Control for Nonlinear Systems Under Uncertainty. arXiv:200206006. 2020.
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2019 | Conference Paper | LibreCat-ID: 13107
Schumacher J, Rezat S. A Hypothetical Learning Trajectory for the Learning of the Rules for Manipulating Integers. In: Jankvist UT, Van den Heuvel-Panhuizen M, Veldhuis M, eds. Proceedings of the Eleventh Congress of the European Society for Research in Mathematics Education (CERME11, February 6 – 10, 2019). Utrecht, the Netherlands: Freudenthal Group & Freudenthal Institute, Utrecht University and ERME.
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2019 | Journal Article | LibreCat-ID: 10595
Gebken B, Peitz S, Dellnitz M. On the hierarchical structure of Pareto critical sets. Journal of Global Optimization. 2019;73(4):891-913. doi:10.1007/s10898-019-00737-6
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| DOI
2019 | Preprint | LibreCat-ID: 16295
Gebken B, Peitz S. Inverse multiobjective optimization: Inferring decision criteria from data. arXiv:190106141. 2019.
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2019 | Book Chapter | LibreCat-ID: 13108
Schumacher J, Rezat S. Rekonstruktion diagrammatischen Schließens beim Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer Zugänge. In: Kadunz G, ed. Semiotische Perspektiven auf das Lernen von Mathematik II. Springer.
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