Data-driven approximation of the Koopman generator: Model reduction, system identification, and control

23 September 2019

Papers citing "Data-driven approximation of the Koopman generator: Model reduction, system identification, and control"

27 / 27 papers shown

Title
Physics-informed Split Koopman Operators for Data-efficient Soft Robotic Simulation Eron Ristich Lei Zhang Yi Ren Jiefeng Sun 60 0 0 31 Jan 2025
Learning Koopman-based Stability Certificates for Unknown Nonlinear Systems Ruikun Zhou Yiming Meng Zhexuan Zeng Jun Liu 80 0 0 03 Dec 2024
Kernel-Based Optimal Control: An Infinitesimal Generator Approach Petar Bevanda Nicolas Hosichen Tobias Wittmann Jan Brüdigam Sandra Hirche Boris Houska 79 0 0 02 Dec 2024
On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions Jake Buzhardt C. Ricardo Constante-Amores Michael D. Graham 73 2 0 20 Nov 2024
From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach Timothée Devergne Vladimir Kostic Michele Parrinello Massimiliano Pontil 32 3 0 13 Jun 2024
Dynamical systems and complex networks: A Koopman operator perspective Stefan Klus Natavsa Djurdjevac Conrad 18 2 0 14 May 2024
Koopman-Assisted Reinforcement Learning Preston Rozwood Edward Mehrez Ludger Paehler Wen Sun Steven L. Brunton 40 6 0 04 Mar 2024
Simplicity bias, algorithmic probability, and the random logistic map B. Hamzi K. Dingle 28 3 0 31 Dec 2023
Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder Priyam Gupta Peter J. Schmid D. Sipp T. Sayadi Georgios Rigas 19 5 0 16 Oct 2023
Transfer operators on graphs: Spectral clustering and beyond Stefan Klus Maia Trower 22 5 0 19 May 2023
Safe and Stable Control Synthesis for Uncertain System Models via Distributionally Robust Optimization Kehan Long Yinzhuang Yi Jorge Cortés Nikolay Atanasov 22 9 0 04 Oct 2022
One-Shot Learning of Stochastic Differential Equations with Data Adapted Kernels Matthieu Darcy B. Hamzi Giulia Livieri H. Owhadi P. Tavallali 36 26 0 24 Sep 2022
Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories Samuel E. Otto Sebastian Peitz C. Rowley 31 19 0 20 Sep 2022
Ensemble forecasts in reproducing kernel Hilbert space family Benjamin Dufée Berenger Hug É. Mémin G. Tissot 24 1 0 29 Jul 2022
Residual Dynamic Mode Decomposition: Robust and verified Koopmanism Matthew J. Colbrook Lorna J. Ayton Máté Szőke 35 58 0 19 May 2022
An end-to-end deep learning approach for extracting stochastic dynamical systems with $α$ -stable Lévy noise Cheng Fang Yubin Lu Ting Gao Jinqiao Duan 55 16 0 31 Jan 2022
Towards Data-driven LQR with Koopmanizing Flows Petar Bevanda Maximilian Beier Shahab Heshmati-alamdari Stefan Sosnowski Sandra Hirche 13 4 0 27 Jan 2022
Rigorous data-driven computation of spectral properties of Koopman operators for dynamical systems Matthew J. Colbrook Alex Townsend 26 67 0 29 Nov 2021
Deeptime: a Python library for machine learning dynamical models from time series data Moritz Hoffmann Martin K. Scherer Tim Hempel Andreas Mardt Brian M. de Silva ... Stefan Klus Hao Wu N. Kutz Steven L. Brunton Frank Noé AI4CE 33 101 0 28 Oct 2021
Learning the Koopman Eigendecomposition: A Diffeomorphic Approach Petar Bevanda Johannes Kirmayr Stefan Sosnowski Sandra Hirche 38 9 0 15 Oct 2021
Extracting Stochastic Governing Laws by Nonlocal Kramers-Moyal Formulas Yubin Lu Yang Li Jinqiao Duan 21 16 0 28 Aug 2021
Convergence Rates for Learning Linear Operators from Noisy Data Maarten V. de Hoop Nikola B. Kovachki Nicholas H. Nelsen Andrew M. Stuart 21 54 0 27 Aug 2021
Extracting Governing Laws from Sample Path Data of Non-Gaussian Stochastic Dynamical Systems Yang Li Jinqiao Duan 14 16 0 21 Jul 2021
Modern Koopman Theory for Dynamical Systems Steven L. Brunton M. Budišić E. Kaiser J. Nathan Kutz AI4CE 46 400 0 24 Feb 2021
Data-driven model reduction of agent-based systems using the Koopman generator Jan-Hendrik Niemann Stefan Klus Christof Schütte 12 9 0 14 Dec 2020
Kernel methods for center manifold approximation and a data-based version of the Center Manifold Theorem B. Haasdonk B. Hamzi G. Santin D. Wittwar 26 21 0 01 Dec 2020
A convex data-driven approach for nonlinear control synthesis Hyungjin Choi Umesh Vaidya Yongxin Chen 9 13 0 28 Jun 2020