most citedGroup-Convolutional Extended Dynamic Mode Decomposition

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

math.DS2026

Numerical approximation of the Koopman-von Neumann equation: Operator learning and quantum computing

Stefan Klus, Feliks Nüske, Patrick Gelß

The Koopman-von Neumann equation describes the evolution of wavefunctions associated with autonomous ordinary differential equations and can be regarded as a quantum physics-inspir…

physics.chem-ph2024

Thermodynamic Interpolation: A generative approach to molecular thermodynamics and kinetics

Selma Moqvist, Weilong Chen, Mathias Schreiner +2

Using normalizing flows and reweighting, Boltzmann Generators enable equilibrium sampling from a Boltzmann distribution, defined by an energy function and thermodynamic state. In t…

math.DS20242 cited

Group-Convolutional Extended Dynamic Mode Decomposition

Hans Harder, Feliks Nüske, Friedrich M. Philipp +3

This paper explores the integration of symmetries into the Koopman-operator framework for the analysis and efficient learning of equivariant dynamical systems using a group-convolu…

math.OC2024

Koopman-based Control for Stochastic Systems: Application to Enhanced Sampling

Lei Guo, Jan Heiland, Feliks Nüske

We present a data-driven approach to use the Koopman generator for prediction and optimal control of control-affine stochastic systems. We provide a novel conceptual approach and a…

physics.comp-ph2024

Kinetically Consistent Coarse Graining using Kernel-based Extended Dynamic Mode Decomposition

Vahid Nateghi, Feliks Nüske

In this paper, we show how kernel-based models for the Koopman generator -- the gEDMD method -- can be used to identify coarse-grained dynamics on reduced variables, which retain t…