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228 Publications


2022 | Journal Article | LibreCat-ID: 20731 | OA
Bieker, K., Gebken, B., & Peitz, S. (2022). On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7797–7808. https://doi.org/10.1109/TPAMI.2021.3114962
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2021 | Journal Article | LibreCat-ID: 24169
Nüske, F., Gelß, P., Klus, S., & Clementi, C. (2021). Tensor-based computation of metastable and coherent sets. Physica D: Nonlinear Phenomena, Article 133018. https://doi.org/10.1016/j.physd.2021.133018
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2021 | Journal Article | LibreCat-ID: 24170
Klus, S., Gelß, P., Nüske, F., & Noé, F. (2021). Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Machine Learning: Science and Technology, Article 045016. https://doi.org/10.1088/2632-2153/ac14ad
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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: 21337 | OA
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 | OA
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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2021 | Journal Article | LibreCat-ID: 16867 | OA
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: 16295 | OA
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 | Dissertation | LibreCat-ID: 32057 | OA
Gerlach, R. (2021). The Computation and Analysis of Invariant Sets of Infinite-Dimensional Systems. https://doi.org/10.17619/UNIPB/1-1278
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2021 | Journal Article | LibreCat-ID: 16294 | OA
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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2020 | Book Chapter | LibreCat-ID: 17411
Flaßkamp, K., Ober-Blöbaum, S., & Peitz, S. (2020). Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach. In O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum, & K. Padberg-Gehle (Eds.), Advances in Dynamics, Optimization and Computation. Cham: Springer. https://doi.org/10.1007/978-3-030-51264-4_9
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2020 | Journal Article | LibreCat-ID: 21819 | OA
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 | 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 | 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 | Journal Article | LibreCat-ID: 16290 | OA
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 | 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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2020 | Journal Article | LibreCat-ID: 16710 | OA
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: 16297
Hernández Castellanos, C. I., Ober-Blöbaum, S., & Peitz, S. (2020). Explicit Multi-objective Model Predictive Control for Nonlinear Systems  Under Uncertainty. International Journal of Robust and Nonlinear Control, 30(17), 7593–7618. https://doi.org/10.1002/rnc.5197
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2020 | Book Chapter | LibreCat-ID: 17994
Gerlach, R., & Ziessler, A. (2020). The Approximation of Invariant Sets in Infinite Dimensional Dynamical Systems. In O. Junge, O. Schütze, S. Ober-Blöbaum, & K. Padberg-Gehle (Eds.), Advances in Dynamics, Optimization and Computation (Vol. 304, pp. 66–85). Springer International Publishing. https://doi.org/10.1007/978-3-030-51264-4_3
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2020 | Journal Article | LibreCat-ID: 16712
Dellnitz, M., Gebken, B., Gerlach, R., & Klus, S. (2020). On the equivariance properties of self-adjoint matrices. Dynamical Systems, 35(2), 197–215. https://doi.org/10.1080/14689367.2019.1661355
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2019 | Journal Article | LibreCat-ID: 21944
Nüske, F., Boninsegna, L., & Clementi, C. (2019). Coarse-graining molecular systems by spectral matching. The Journal of Chemical Physics. https://doi.org/10.1063/1.5100131
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2019 | Journal Article | LibreCat-ID: 16709
Sahai, T., Ziessler, A., Klus, S., & Dellnitz, M. (2019). Continuous relaxations for the traveling salesman problem. Nonlinear Dynamics. https://doi.org/10.1007/s11071-019-05092-5
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2019 | Journal Article | LibreCat-ID: 10593
Peitz, S., & Klus, S. (2019). Koopman operator-based model reduction for switched-system control of PDEs. Automatica, 106, 184–191. https://doi.org/10.1016/j.automatica.2019.05.016
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2019 | Journal Article | LibreCat-ID: 10595
Gebken, B., Peitz, S., & Dellnitz, M. (2019). On the hierarchical structure of Pareto critical sets. Journal of Global Optimization, 73(4), 891–913. https://doi.org/10.1007/s10898-019-00737-6
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2019 | Conference Paper | LibreCat-ID: 10597
Hanke, S., Peitz, S., Wallscheid, O., Böcker, J., & Dellnitz, M. (2019). Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous Motor Application with Online Least Squares System Identification. In 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE). https://doi.org/10.1109/precede.2019.8753313
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2019 | Preprint | LibreCat-ID: 16711 | OA
Gerlach, R., Koltai, P., & Dellnitz, M. (2019). Revealing the intrinsic geometry of finite dimensional invariant sets of  infinite dimensional dynamical systems. In arXiv:1902.08824.
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2019 | Journal Article | LibreCat-ID: 16708
Ziessler, A., Dellnitz, M., & Gerlach, R. (2019). The Numerical Computation of Unstable Manifolds for Infinite Dimensional Dynamical Systems by Embedding Techniques. SIAM Journal on Applied Dynamical Systems, 18(3), 1265–1292. https://doi.org/10.1137/18m1204395
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2018 | Preprint | LibreCat-ID: 21634 | OA
Hanke, S., Peitz, S., Wallscheid, O., Klus, S., Böcker, J., & Dellnitz, M. (2018). Koopman Operator-Based Finite-Control-Set Model Predictive Control for  Electrical Drives. ArXiv:1804.00854.
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2018 | Journal Article | LibreCat-ID: 21940
Litzinger, F., Boninsegna, L., Wu, H., Nüske, F., Patel, R., Baraniuk, R., … Clementi, C. (2018). Rapid Calculation of Molecular Kinetics Using Compressed Sensing. Journal of Chemical Theory and Computation, 2771–2783. https://doi.org/10.1021/acs.jctc.8b00089
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2018 | Journal Article | LibreCat-ID: 21941
Klus, S., Nüske, F., Koltai, P., Wu, H., Kevrekidis, I., Schütte, C., & Noé, F. (2018). Data-Driven Model Reduction and Transfer Operator Approximation. Journal of Nonlinear Science, 985–1010. https://doi.org/10.1007/s00332-017-9437-7
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2018 | Journal Article | LibreCat-ID: 21942
Boninsegna, L., Nüske, F., & Clementi, C. (2018). Sparse learning of stochastic dynamical equations. The Journal of Chemical Physics. https://doi.org/10.1063/1.5018409
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2018 | Journal Article | LibreCat-ID: 21943
Hruska, E., Abella, J. R., Nüske, F., Kavraki, L. E., & Clementi, C. (2018). Quantitative comparison of adaptive sampling methods for protein dynamics. The Journal of Chemical Physics. https://doi.org/10.1063/1.5053582
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2018 | Conference Paper | LibreCat-ID: 8750
Gebken, B., Peitz, S., & Dellnitz, M. (2018). A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems. In Numerical and Evolutionary Optimization – NEO 2017. Cham. https://doi.org/10.1007/978-3-319-96104-0_2
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2018 | Journal Article | LibreCat-ID: 8751 | OA
Peitz, S., & Dellnitz, M. (2018). A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models, Feedback Control and Objective Reduction. Mathematical and Computational Applications, 23(2). https://doi.org/10.3390/mca23020030
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2018 | Book Chapter | LibreCat-ID: 8754
Beermann, D., Dellnitz, M., Peitz, S., & Volkwein, S. (2018). Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition. In Reduced-Order Modeling (ROM) for Simulation and Optimization (pp. 47–72). Cham. https://doi.org/10.1007/978-3-319-75319-5_3
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2018 | Journal Article | LibreCat-ID: 8755
Klus, S., Gelß, P., Peitz, S., & Schütte, C. (2018). Tensor-based dynamic mode decomposition. Nonlinearity, 31(7), 3359–3380. https://doi.org/10.1088/1361-6544/aabc8f
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2018 | Conference Paper | LibreCat-ID: 8757
Beermann, D., Dellnitz, M., Peitz, S., & Volkwein, S. (2018). POD-based multiobjective optimal control of PDEs with non-smooth objectives. In PAMM (pp. 51–54). https://doi.org/10.1002/pamm.201710015
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2018 | Journal Article | LibreCat-ID: 16713
Gölz, C., Voelcker-Rehage, C., Mora, K., Reuter, E.-M., Godde, B., Dellnitz, M., … Vieluf, S. (2018). Improved Neural Control of Movements Manifests in Expertise-Related Differences in Force Output and Brain Network Dynamics. Frontiers in Physiology. https://doi.org/10.3389/fphys.2018.01540
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2018 | Journal Article | LibreCat-ID: 16714
Vieluf, S., Mora, K., Gölz, C., Reuter, E.-M., Godde, B., Dellnitz, M., … Voelcker-Rehage, C. (2018). Age- and Expertise-Related Differences of Sensorimotor Network Dynamics during Force Control. Neuroscience, 203–213. https://doi.org/10.1016/j.neuroscience.2018.07.025
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2018 | Journal Article | LibreCat-ID: 16715
Bittracher, A., Koltai, P., Klus, S., Banisch, R., Dellnitz, M., & Schütte, C. (2018). Transition Manifolds of Complex Metastable Systems. Journal of Nonlinear Science, 28, 471–512. https://doi.org/10.1007/s00332-017-9415-0
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2018 | Preprint | LibreCat-ID: 16292 | OA
Peitz, S. (2018). Controlling nonlinear PDEs using low-dimensional bilinear approximations  obtained from data. ArXiv:1801.06419.
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2018 | Preprint | LibreCat-ID: 16293 | OA
Klus, S., Peitz, S., & Schuster, I. (2018). Analyzing high-dimensional time-series data using kernel transfer  operator eigenfunctions. ArXiv:1805.10118.
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2018 | Journal Article | LibreCat-ID: 8753
Peitz, S., Ober-Blöbaum, S., & Dellnitz, M. (2018). Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling. Acta Applicandae Mathematicae, 161(1), 171–199. https://doi.org/10.1007/s10440-018-0209-7
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2017 | Journal Article | LibreCat-ID: 21938
Nüske, F., Wu, H., Prinz, J.-H., Wehmeyer, C., Clementi, C., & Noé, F. (2017). Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias. The Journal of Chemical Physics. https://doi.org/10.1063/1.4976518
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2017 | Journal Article | LibreCat-ID: 21939
Wu, H., Nüske, F., Paul, F., Klus, S., Koltai, P., & Noé, F. (2017). Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations. The Journal of Chemical Physics. https://doi.org/10.1063/1.4979344
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2017 | Conference Paper | LibreCat-ID: 8752
Peitz, S., & Dellnitz, M. (2017). Gradient-Based Multiobjective Optimization with Uncertainties. In NEO 2016 (pp. 159–182). Cham. https://doi.org/10.1007/978-3-319-64063-1_7
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2017 | Journal Article | LibreCat-ID: 16540
Dellnitz, M., & Klus, S. (2017). Sensing and control in symmetric networks. Dynamical Systems, 61–79. https://doi.org/10.1080/14689367.2016.1215410
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2017 | Journal Article | LibreCat-ID: 16581
Dellnitz, M., Klus, S., & Ziessler, A. (2017). A Set-Oriented Numerical Approach for Dynamical Systems with Parameter Uncertainty. SIAM Journal on Applied Dynamical Systems, 120–138. https://doi.org/10.1137/16m1072735
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2017 | Journal Article | LibreCat-ID: 16657
Peitz, S., Schäfer, K., Ober-Blöbaum, S., Eckstein, J., Köhler, U., & Dellnitz, M. (2017). A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles * *This research was funded by the German Federal Ministry of Education and Research (BMBF) within the Leading-Edge Cluster Intelligent Technical Systems OstWestfalenLippe (it’s OWL). IFAC-PapersOnLine, 8674–8679. https://doi.org/10.1016/j.ifacol.2017.08.1526
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