518 citations · 1.5k across the 21 of their papers we have counts for
4 papers · 1 filter
Deeptime: a Python library for machine learning dynamical models from time series data
Moritz Hoffmann, Martin Scherer, Tim Hempel +8
Generation and analysis of time-series data is relevant to many quantitative fields ranging from economics to fluid mechanics. In the physical sciences, structures such as metastab…
Kernel Embedding based Variational Approach for Low-dimensional Approximation of Dynamical Systems
Wenchong Tian, Hao Wu
Transfer operators such as Perron-Frobenius or Koopman operator play a key role in modeling and analysis of complex dynamical systems, which allow linear representations of nonline…
Optimal data-driven estimation of generalized Markov state models for non-equilibrium dynamics
Péter Koltai, Hao Wu, Frank Noé +1
There are multiple ways in which a stochastic system can be out of statistical equilibrium. It might be subject to time-varying forcing; or be in a transient phase on its way towar…
Data-driven model reduction and transfer operator approximation
Stefan Klus, Feliks Nüske, Péter Koltai +4
In this review paper, we will present different data-driven dimension reduction techniques for dynamical systems that are based on transfer operator theory as well as methods to ap…