Feliks Nüske
Feliks Nüske
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
Verified email at - Homepage
Cited by
Cited by
A variational approach to modeling slow processes in stochastic dynamical systems
F Noé, F Nuske
Multiscale Modeling & Simulation 11 (2), 635-655, 2013
Variational approach to molecular kinetics
F Nüske, BG Keller, G Pérez-Hernández, ASJS Mey, F Noé
Journal of chemical theory and computation 10 (4), 1739-1752, 2014
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, 985-1010, 2018
Sparse learning of stochastic dynamical equations
L Boninsegna, F Nüske, C Clementi
The Journal of chemical physics 148 (24), 2018
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
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), 2017
Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias
F Nüske, H Wu, JH Prinz, C Wehmeyer, C Clementi, F Noé
The Journal of Chemical Physics 146 (9), 2017
Quantitative comparison of adaptive sampling methods for protein dynamics
E Hruska, JR Abella, F Nüske, LE Kavraki, C Clementi
The Journal of chemical physics 149 (24), 2018
Variational tensor approach for approximating the rare-event kinetics of macromolecular systems
F Nüske, R Schneider, F Vitalini, F Noé
The Journal of chemical physics 144 (5), 2016
Finite-data error bounds for Koopman-based prediction and control
F Nüske, S Peitz, F Philipp, M Schaller, K Worthmann
Journal of Nonlinear Science 33 (1), 14, 2023
Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator
S Klus, F Nüske, B Hamzi
Entropy 22 (7), 722, 2020
Coarse-graining molecular systems by spectral matching
F Nüske, L Boninsegna, C Clementi
The Journal of chemical physics 151 (4), 2019
Rapid calculation of molecular kinetics using compressed sensing
F Litzinger, L Boninsegna, H Wu, F Nüske, R Patel, R Baraniuk, F Noé, ...
Journal of chemical theory and computation 14 (5), 2771-2783, 2018
Koopman analysis of quantum systems
S Klus, F Nüske, S Peitz
J. Phys. A: Math. Theor. 55, 314002, 2022
Tensor-based computation of metastable and coherent sets
F Nüske, P Gelß, S Klus, C Clementi
Physica D: Nonlinear Phenomena 427, 133018, 2021
Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry
S Klus, P Gelß, F Nüske, F Noé
Machine Learning: Science and Technology 2 (4), 045016, 2021
Towards reliable data-based optimal and predictive control using extended DMD
M Schaller, K Worthmann, F Philipp, S Peitz, F Nüske
IFAC-PapersOnLine 56 (1), 169-174, 2023
Error bounds for kernel-based approximations of the Koopman operator
FM Philipp, M Schaller, K Worthmann, S Peitz, F Nüske
Applied and Computational Harmonic Analysis 71, 101657, 2024
Spectral properties of effective dynamics from conditional expectations
F Nüske, P Koltai, L Boninsegna, C Clementi
Entropy 23 (2), 134, 2021
Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular Kinetics
W Yang, C Templeton, D Rosenberger, A Bittracher, F Nüske, F Noé, ...
ACS Central Science 9 (2), 186-196, 2023
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