274 citations · 409 across the 17 of their papers we have counts for
17 papers
Effective Dynamics and Transition Pathways from Koopman-Inspired Neural Learning of Collective Variables
Alexander Sikorski, Luca Donati, Marcus Weber +1
The ISOKANN (Invariant Subspaces of Koopman Operators Learned by Artificial Neural Networks) framework provides a data-driven route to extract collective variables (CVs) and effect…
On-the-Fly Lifting of Coarse Reaction-Coordinate Paths to Full-Dimensional Transition Path Ensembles
Christof Schütte, Alexander Sikorski, Jakob Kresse +1
Effective dynamics on a low-dimensional collective-variable (CV) or latent space can be simulated far more cheaply than the underlying high-dimensional stochastic system, but explo…
Existence of Multilateral Nash equilibria for families of games
Matija Blagojevic, Christof Schütte
This paper introduces two fundamentally new concepts to game theory: multilateral Nash equilibria and families of games. Starting with non-cooperative games, we show how these noti…
Data-driven Reduction of Transfer Operators for Particle Clustering Dynamics
Nathalie Wehlitz, Grigorios A. Pavliotis, Christof Schütte +1
We develop an operator-based framework to coarse-grain interacting particle systems that exhibit clustering dynamics. Starting from the particle-based transfer operator, we first c…
Mean-field optimal control with stochastic leaders
Sebastian Zimper, Ana Djurdjevac, Carsten Hartmann +2
We consider interacting agent systems with a large number of stochastic agents influenced by a fixed number of external stochastic lead agents. Such settings arise, for example in…
Generative modeling of conditional probability distributions on the level-sets of collective variables
Fatima-Zahrae Akhyar, Wei Zhang, Gabriel Stoltz +1
Given a probability distribution in represented by data, we study in this paper the generative modeling of the corresponding conditional probability distribution…