M. Schaller, K. Worthmann, F. Philipp, S. Peitz, and F. Nüske, “Towards reliable data-based optimal and predictive control using extended DMD,”10.1016/j.ifacol.2023.02.029__in IFAC-PapersOnLine, 2023, vol. 56, no. 1, pp. 169–174, doi:10.1016/j.ifacol.2023.02.029 .
LibreCat: /record/30125
DOI: 10.1016/j.ifacol.2023.02.029
arXiv: 2202.09084

F. Nüske, S. Peitz, F. Philipp, M. Schaller, and K. Worthmann, “Finite-data error bounds for Koopman-based prediction and control,”10.1007/s00332-022-09862-1__Journal of Nonlinear Science, vol. 33, Art. no. 14, 2023, doi:10.1007/s00332-022-09862-1 .
LibreCat: /record/23428
DOI: 10.1007/s00332-022-09862-1

S. Klus, F. Nüske, and S. Peitz, “Koopman analysis of quantum systems,”10.1088/1751-8121/ac7d22__Journal of Physics A: Mathematical and Theoretical, vol. 55, no. 31, p. 314002, 2022, doi:10.1088/1751-8121/ac7d22 .
LibreCat: /record/29673
DOI: 10.1088/1751-8121/ac7d22
arXiv: 2201.12062

F. Nüske, P. Gelß, S. Klus, and C. Clementi, “Tensor-based computation of metastable and coherent sets,”10.1016/j.physd.2021.133018__Physica D: Nonlinear Phenomena, Art. no. 133018, 2021, doi:10.1016/j.physd.2021.133018 .
LibreCat: /record/24169
DOI: 10.1016/j.physd.2021.133018

S. Klus, P. Gelß, F. Nüske, and F. Noé, “Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry,”10.1088/2632-2153/ac14ad__Machine Learning: Science and Technology, Art. no. 045016, 2021, doi:10.1088/2632-2153/ac14ad .
LibreCat: /record/24170
DOI: 10.1088/2632-2153/ac14ad

F. Nüske, P. Koltai, L. Boninsegna, and C. Clementi, “Spectral Properties of Effective Dynamics from Conditional Expectations,” Entropy, 2021.
LibreCat: /record/21820
DOI: 10.3390/e23020134

S. Klus, F. Nüske, and B. Hamzi, “Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator,” Entropy, 2020.
LibreCat: /record/21819
DOI: 10.3390/e22070722

S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, and C. Schütte, “Data-driven approximation of the Koopman generator: Model reduction, system identification, and control,” Physica D: Nonlinear Phenomena, vol. 406, 2020.
LibreCat: /record/16288
DOI: 10.1016/j.physd.2020.132416

F. Nüske, L. Boninsegna, and C. Clementi, “Coarse-graining molecular systems by spectral matching,” The Journal of Chemical Physics, 2019.
LibreCat: /record/21944
DOI: 10.1063/1.5100131

F. Litzinger et al., “Rapid Calculation of Molecular Kinetics Using Compressed Sensing,” Journal of Chemical Theory and Computation, pp. 2771–2783, 2018.
LibreCat: /record/21940
DOI: 10.1021/acs.jctc.8b00089

S. Klus et al., “Data-Driven Model Reduction and Transfer Operator Approximation,” Journal of Nonlinear Science, pp. 985–1010, 2018.
LibreCat: /record/21941
DOI: 10.1007/s00332-017-9437-7

L. Boninsegna, F. Nüske, and C. Clementi, “Sparse learning of stochastic dynamical equations,” The Journal of Chemical Physics, 2018.
LibreCat: /record/21942
DOI: 10.1063/1.5018409

E. Hruska, J. R. Abella, F. Nüske, L. E. Kavraki, and C. Clementi, “Quantitative comparison of adaptive sampling methods for protein dynamics,” The Journal of Chemical Physics, 2018.
LibreCat: /record/21943
DOI: 10.1063/1.5053582

F. Nüske, H. Wu, J.-H. Prinz, C. Wehmeyer, C. Clementi, and F. Noé, “Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias,” The Journal of Chemical Physics, 2017.
LibreCat: /record/21938
DOI: 10.1063/1.4976518

H. Wu, F. Nüske, F. Paul, S. Klus, P. Koltai, and F. Noé, “Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations,” The Journal of Chemical Physics, 2017.
LibreCat: /record/21939
DOI: 10.1063/1.4979344

F. Nüske, R. Schneider, F. Vitalini, and F. Noé, “Variational tensor approach for approximating the rare-event kinetics of macromolecular systems,” The Journal of Chemical Physics, 2016.
LibreCat: /record/21937
DOI: 10.1063/1.4940774

F. Nüske, B. G. Keller, G. Pérez-Hernández, A. S. J. S. Mey, and F. Noé, “Variational Approach to Molecular Kinetics,” Journal of Chemical Theory and Computation, pp. 1739–1752, 2014.
LibreCat: /record/21936
DOI: 10.1021/ct4009156

F. Noé and F. Nüske, “A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems,” Multiscale Modeling &; Simulation, pp. 635–655, 2013.
LibreCat: /record/21935
DOI: 10.1137/110858616