Publications DMP group

Berger, T.; Nüske, F.: Funnel Control for Langevin Dynamics. Automatica 179, 112448 (2025)

Cao, S.; Nüske, F.; Liu, B.; Soley, M.; Huang, X.: AMUSET-TICA: A Tensor-Based Approach for Identifying Slow Collective Variables in Biomolecular Dynamics. Journal of Chemical Theory and Computation 21 (9), pp. 4855 - 4866 (2025)

Harder, H.; Peitz, S.; Nüske, F.; Philipp, F. M.; Schaller, M.; Worthmann, K.: Group-Convolutional Extended Dynamic Mode Decomposition. Physica D: Nonlinear Phenomena 480, 134725 (2025)

Moqvist, S.; Chen, W.; Schreiner, M.; Nüske, F.; Olsson, S.: Thermodynamic Interpolation: A generative approach to molecular thermodynamics and kinetics. Journal of Chemical Theory and Computation 21 (5), pp. 2535 - 2545 (2025)

Nateghi, V.; Nüske, F.: Kinetically Consistent Coarse Graining using Kernel-based Extended Dynamic Mode Decomposition. Journal of Chemical Theory and Computation 21 (15), pp. 7236 - 7248 (2025)

Peitz, S.; Harder, H.; Nüske, F.; Philipp, F.; Schaller, M.; Worthmann, K.: Equivariance and partial observations in Koopman operator theory for partial differential equations. Journal of Computational Dynamics 12 (2), pp. 305 - 324 (2025)

Philipp, F.; Schaller, M.; Worthmann, K.; Peitz, S.; Nüske, F.: Error analysis of kernel EDMD for prediction and control in the Koopman framework. Journal of Nonlinear Science 35, 92 (2025)

Philipp, F.; Schaller, M.; Worthmann, K.; Peitz, S.; Nüske, F.: Error bounds for kernel-based approximations of the Koopman operator. Applied and Computational Harmonic Analysis 71, 101657 (2024)

Nateghi, V.; Manzi, M.: Machine learning methods for nonlinear dimensionality reduction of the thermospheric density field. Advances in Space Research 72 (10), pp. 4106 - 4114 (2023)

Nüske, F.; Klus, S.: Efficient Approximation of Molecular Kinetics using Random Fourier Features. The Journal of Chemical Physics 159 (7), 074105 (2023)

Nüske, F.; Peitz, S.; Philipp, F.; Schaller, M.; Worthmann, K.: Finite-data error bounds for Koopman-based prediction and control. Journal of Nonlinear Science 33, 14 (2023)

Yang, W.; Templeton, C.; Rosenberger, D.; Bittracher, A.; Nüske, F.; Noé, F.; Clementi, C.: Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular Kinetics. ACS Central Science 9 (2), pp. 186 - 196 (2023)

Klus, S.; Nüske, F.; Peitz, S.: Koopman analysis of quantum systems. Journal of Physics A 55, 314002 (2022)

Lücke, M.; Nüske, F.: tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format. Journal of Nonlinear Science 32, 44 (2022)

Guo, L.; Heiland, J.; Nüske, F.: Koopman-based Control for Stochastic Systems: Application to Enhanced Sampling. 11th Vienna International Conference on Mathematical Modelling MATHMOD 2025 , Vienna, Austria, February 19, 2025 - February 21, 2025. IFAC-PapersOnLine 59 (1), pp. 283 - 288 (2025)

Philipp, F.; Schaller, M.; Worthmann, K.; Peitz, S.; Nüske, F.: Invariance of Gaussian RKHSs under Koopman operators of stochastic differential equations with constant matrix coefficients. Proceedings in Applied Mathematics and Mechanics 25 (1), e202400127, (2025)

Schaller, M.; Worthmann, K.; Philipp, F.; Peitz, S.; Nüske, F.: Towards reliable data-based optimal and predictive control using extended DMD. 12th IFAC Symposium on Nonlinear Control Systems NOLCOS 2022, Canberra, Australia, January 04, 2023 - January 06, 2023. IFAC-PapersOnLine 56 (1), pp. 169 - 174 (2023)

Nateghi, V.; Neureither, L.; Moqvist, S.; Hartmann, C.; Olsson, S.; Nüske, F.: Consistent Projection of Langevin Dynamics: Preserving Thermodynamics and Kinetics in Coarse-Grained Models. (2025)

Sprink, H.; Zhu, Y.; Mey, A. S.J.S.; Nüske, F.: Accurate and Robust Analysis of Molecular Kinetics with Random Features. (2025)

Philipp, F. M.; Schaller, M.; Boshoff, S.; Peitz, S.; Nüske, F.; Worthmann, K.: Extended Dynamic Mode Decomposition: Sharp bounds on the sample efficiency. (2024)