| Login | Create Account |
Browse by Authors
Group by: Date | Item Type Number of items: 15. 2023Schütte, Christof and Klus, Stefan and Hartmann, Carsten (2023) Overcoming the Timescale Barrier in Molecular Dynamics: Transfer Operators, Variational Principles, and Machine Learning. Acta Numerica, 32 . pp. 517-673. 2022Mollenhauer, Mattes and Klus, Stefan and Schütte, Christof and Koltai, Péter (2022) Kernel autocovariance operators of stationary processes: Estimation and convergence. Journal of Machine Learning Research, 23 (327). pp. 1-34. 2021Hoffmann, Moritz and Scherer, Martin and Hempel, Tim and Mardt, Andreas and de Silva, Brian and Husic, Brooke E. and Klus, Stefan and Wu, Hao and Kutz, Nathan and Brunton, Steven L (2021) Deeptime: a Python library for machine learning dynamical models from time series data. Mach. Learn.: Sci. Technol. 3 (2022), 3 (015009). pp. 1-28. Klus, Stefan and Gelß, Patrick and Nüske, Feliks and Noé, Frank (2021) Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Machine Learning: Science and Technologie, 2 . pp. 1-23. Gelß, Patrick and Klus, Stefan and Schuster, Ingmar and Schütte, Christof (2021) Feature space approximation for kernel-based supervised learning. Knowledge-Based Systems, 221 . Niemann, Jan-Hendrik and Klus, Stefan and Schütte, Christof (2021) Data-driven model reduction of agent-based systems using the Koopman generator. PLOS ONE, 16 (5). 2020Bittracher, Andreas and Klus, Stefan and Hamzi, Boumediene and Koltai, Péter and Schütte, Christof (2020) Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds. Journal of Nonlinear Science, 31 (3). pp. 1-41. ISSN 1432-1467 (online) Bittracher, Andreas and Klus, Stefan and Hamzi, Boumediene and Koltai, Péter and Schütte, Christof (2020) Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds. Journal of Nonlinear Science, 31 (3). Klus, Stefan and Nüske, Felix and Hamzi, Boumediene (2020) Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator. entropy, 22 . Klus, Stefan (2020) Data-driven analysis of complex dynamical systems. Refubium . pp. 1-174. Klus, Stefan and Nüske, Feliks and Peitz, Sebastian and Niemann, Jan-Hendrik and Clementi, Cecilia and Schütte, Christof (2020) Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena, 406 (132416). Schuster, Ingmar and Mollenhauer, Mattes and Klus, Stefan and Muandet, K. (2020) Kernel Conditional Density Operators. In: 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), August 26 - 28, 2020, Online. Mollenhauer, Mattes and Schuster, Ingmar and Klus, Stefan and Schütte, Christof (2020) Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces. Advances in Dynamics, Optimization and Computation . pp. 109-131. 2019Klus, Stefan and Husic, Brooke E. and Mollenhauer, Mattes and Noé, Frank (2019) Kernel methods for detecting coherent structures in dynamical data. Chaos, 29 (12). 2018Klus, Stefan and Bittracher, Andreas and Schuster, Ingmar and Schütte, Christof (2018) A kernel-based approach to molecular conformation analysis. Journal of Chemical Physics, 149 (244109). |
