On the numerical approximation of the Perron-Frobenius and Koopman operator S Klus, P Koltai, C Schütte arXiv preprint arXiv:1512.05997, 2015 | 146 | 2015 |

On the numerical approximation of the Perron-Frobenius and Koopman operator S Klus, P Koltai, C Schütte arXiv preprint arXiv:1512.05997, 2015 | 146 | 2015 |

Data-driven model reduction and transfer operator approximation S Klus, F Nüske, P Koltai, H Wu, I Kevrekidis, C Schütte, F Noé Journal of Nonlinear Science 28 (3), 985-1010, 2018 | 145 | 2018 |

Koopman operator-based model reduction for switched-system control of PDEs S Peitz, S Klus Automatica 106, 184-191, 2019 | 90 | 2019 |

Variational Koopman models: slow collective variables and molecular kinetics from short off-equilibrium simulations H Wu, F Nüske, F Paul, S Klus, P Koltai, F Noé The Journal of chemical physics 146 (15), 154104, 2017 | 70 | 2017 |

Tensor-based dynamic mode decomposition S Klus, P Gelß, S Peitz, C Schütte Nonlinearity 31 (7), 3359, 2018 | 52 | 2018 |

Eigendecompositions of transfer operators in reproducing kernel Hilbert spaces S Klus, I Schuster, K Muandet Journal of Nonlinear Science 30 (1), 283-315, 2020 | 49 | 2020 |

Data-driven approximation of the Koopman generator: Model reduction, system identification, and control S Klus, F Nüske, S Peitz, JH Niemann, C Clementi, C Schütte Physica D: Nonlinear Phenomena 406, 132416, 2020 | 42 | 2020 |

Transition manifolds of complex metastable systems A Bittracher, P Koltai, S Klus, R Banisch, M Dellnitz, C Schütte Journal of nonlinear science 28 (2), 471-512, 2018 | 29 | 2018 |

Multidimensional approximation of nonlinear dynamical systems P Gelß, S Klus, J Eisert, C Schütte Journal of Computational and Nonlinear Dynamics 14 (6), 2019 | 26 | 2019 |

Koopman Operator-Based Finite-Control-Set Model Predictive Control for Electrical Drives S Hanke, S Peitz, O Wallscheid, S Klus, J Böcker, M Dellnitz arXiv preprint arXiv:1804.00854, 2018 | 21 | 2018 |

A kernel-based approach to molecular conformation analysis S Klus, A Bittracher, I Schuster, C Schütte The Journal of chemical physics 149 (24), 244109, 2018 | 18 | 2018 |

A set-oriented numerical approach for dynamical systems with parameter uncertainty M Dellnitz, S Klus, A Ziessler SIAM Journal on Applied Dynamical Systems 16 (1), 120-138, 2017 | 15 | 2017 |

Tensor-based algorithms for image classification S Klus, P Gelß Algorithms 12 (11), 240, 2019 | 13 | 2019 |

Kernel methods for detecting coherent structures in dynamical data S Klus, BE Husic, M Mollenhauer, F Noé Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (12), 123112, 2019 | 11 | 2019 |

Nearest-neighbor interaction systems in the tensor-train format P Gelß, S Klus, S Matera, C Schütte Journal of Computational Physics 341, 140-162, 2017 | 10 | 2017 |

An efficient algorithm for the parallel solution of high-dimensional differential equations S Klus, T Sahai, C Liu, M Dellnitz Journal of computational and applied mathematics 235 (9), 3053-3062, 2011 | 9 | 2011 |

Singular value decomposition of operators on reproducing kernel Hilbert spaces M Mollenhauer, I Schuster, S Klus, C Schütte Proceedings of the Workshop on Dynamics, Optimization and Computation held …, 2020 | 8 | 2020 |

Kernel conditional density operators I Schuster, M Mollenhauer, S Klus, K Muandet International Conference on Artificial Intelligence and Statistics, 993-1004, 2020 | 7 | 2020 |

Kernel-based approximation of the Koopman generator and Schrödinger operator S Klus, F Nüske, B Hamzi Entropy 22 (7), 722, 2020 | 6 | 2020 |