Error bounds for kernel-based approximations of the Koopman operator

2023/01/20 by Friedrich Philipp, Philipp, Friedrich, Manuel Schaller +7 · 10 citations
Computer Science · Decision Sciences · Physics and Astronomy · #47B32 #47B33 #47D07 #62M15 #Dynamical Systems (math.DS) #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Model Reduction and Neural Networks #Probabilistic and Robust Engineering Design

paper · pdf · doi:10.48550/arxiv.2301.08637

openalex publication_date 2023/01/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This repository contains python scripts and data to re-create the result shown in `Error bounds for kernel-based approximations of the Koopman operator, arxiv:2301.08637` See README for detailed instructions on how to re-create these data.

Cited by

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• Koopman Kalman Filter (KKF): An asymptotically optimal nonlinear filtering algorithm with error bounds and its application to parameter estimation
• Bayesian Transfer Operators in Reproducing Kernel Hilbert Spaces
• Data-Driven State Observers for Measure-Preserving Systems
• An overview of Koopman-based control: From error bounds to closed-loop guarantees
• Robust Control Design and Analysis for Nonlinear Systems with Uncertain Initial Conditions Based on Lifting Linearization
• Exact Finite Koopman Embedding of Block-Oriented Polynomial Systems
• Learning Koopman Models From Data Under General Noise Conditions

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