274 citations · 1.8k across the 48 of their papers we have counts for
52 papers
Functional dynamic mode decomposition: Learning infinite-dimensional systems from data
Stefan Klus, Eirini Ioannou
Dynamic mode decomposition (DMD) is a data-driven method that computes the best linear approximation of the underlying dynamical system and decomposes the dynamics into a superposi…
Graph Isomorphism: Mixed-Integer Convex Optimization from First-Order Methods
Wenjie Xiao, Mathieu Besançon, Patrick Gelß +3
The graph isomorphism (GI) problem, which asks whether two graphs are structurally identical, occupies a unique position in computational complexity -- it is neither known to be so…
Data-driven approximation of transfer operators for mean-field stochastic differential equations
Eirini Ioannou, Stefan Klus, Gonçalo dos Reis
Mean-field stochastic differential equations, also called McKean--Vlasov equations, are the limiting equations of interacting particle systems with fully symmetric interaction pote…
Bayesian Transfer Operators in Reproducing Kernel Hilbert Spaces
Septimus Boshoff, Sebastian Peitz, Stefan Klus
The Koopman operator, as a linear representation of a nonlinear dynamical system, has been attracting attention in many fields of science. Recently, Koopman operator theory has bee…
Continuous optimization methods for the graph isomorphism problem
Stefan Klus, Patrick Gelß
The graph isomorphism problem looks deceptively simple, but although polynomial-time algorithms exist for certain types of graphs such as planar graphs and graphs with bounded degr…
Efficient Approximation of Molecular Kinetics using Random Fourier Features
Feliks Nüske, Stefan Klus
Slow kinetic processes of molecular systems can be analyzed by computing dominant eigenpairs of the Koopman operator or its generator. In this context, the Variational Approach to…