45 citations · 147 across the 71 of their papers we have counts for
4 papers · 2 filters
Error analysis of kernel EDMD for prediction and control in the Koopman framework
Friedrich Philipp, Manuel Schaller, Karl Worthmann +2
Extended Dynamic Mode Decomposition (EDMD) is a popular data-driven method to approximate the Koopman operator for deterministic and stochastic (control) systems. This operator is…
Reprojection methods for Koopman-based modelling and prediction
Pieter van Goor, Robert Mahony, Manuel Schaller +1
Extended Dynamic Mode Decomposition (eDMD) is a powerful tool to generate data-driven surrogate models for the prediction and control of nonlinear dynamical systems in the Koopman…
Equivariance and partial observations in Koopman operator theory for partial differential equations
Sebastian Peitz, Hans Harder, Feliks Nüske +3
The Koopman operator has become an essential tool for data-driven analysis, prediction and control of complex systems. The main reason is the enormous potential of identifying line…
Error bounds for kernel-based approximations of the Koopman operator
Friedrich Philipp, Manuel Schaller, Karl Worthmann +2
We consider the data-driven approximation of the Koopman operator for stochastic differential equations on reproducing kernel Hilbert spaces (RKHS). Our focus is on the estimation…