most citedLearning Interpretable Hierarchical Dynamical Systems Models from Time Series Data

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2026

Topological Out-of-Domain Generalization in Dynamical Systems Reconstruction

Georg Trede, Charlotte Ricarda Doll, Elias Weber +1

Predicting the behavior of dynamical systems (DS) beyond the dynamical and parameter regimes observed in training is a pivotal and essentially unresolved problem in scientific ML.…

cs.LG2024★ 1 cited

Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data

Manuel Brenner, Elias Weber, Georgia Koppe +1

In science, we are often interested in obtaining a generative model of the underlying system dynamics from observed time series. While powerful methods for dynamical systems recons…