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1909.10638
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Data-driven approximation of the Koopman generator: Model reduction, system identification, and control
23 September 2019
Stefan Klus
Feliks Nuske
Sebastian Peitz
Jan-Hendrik Niemann
C. Clementi
Christof Schütte
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Papers citing
"Data-driven approximation of the Koopman generator: Model reduction, system identification, and control"
50 / 69 papers shown
Title
Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders
Fynn Fromme
Christine Allen-Blanchette
Hans Harder
Sebastian Peitz
AI4CE
SyDa
90
0
0
19 May 2025
The Stochastic Occupation Kernel (SOCK) Method for Learning Stochastic Differential Equations
Michael L. Wells
Kamel Lahouel
Bruno Jedynak
62
0
0
16 May 2025
Integrated utilization of equations and small dataset in the Koopman operator: applications to forward and inverse problems
Ichiro Ohta
Shota Koyanagi
Kayo Kinjo
Jun Ohkubo
190
0
0
26 Mar 2025
Physics-informed Split Koopman Operators for Data-efficient Soft Robotic Simulation
Eron Ristich
Lei Zhang
Yi Ren
Jiefeng Sun
94
1
0
31 Jan 2025
Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator
Jonghyeon Lee
B. Hamzi
Boya Hou
H. Owhadi
G. Santin
Umesh Vaidya
137
1
0
21 Dec 2024
Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models
Matteo Tomasetto
Francesco Braghin
Andrea Manzoni
OffRL
AI4CE
157
0
0
13 Dec 2024
Learning Koopman-based Stability Certificates for Unknown Nonlinear Systems
Ruikun Zhou
Yiming Meng
Zhexuan Zeng
Jun Liu
123
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
132
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
165
2
0
20 Nov 2024
Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
Vladimir Kostic
Karim Lounici
Helene Halconruy
Timothée Devergne
P. Novelli
Massimiliano Pontil
73
0
0
18 Oct 2024
An evolutionary approach for discovering non-Gaussian stochastic dynamical systems based on nonlocal Kramers-Moyal formulas
Yang Li
Shengyuan Xu
Jinqiao Duan
50
0
0
29 Sep 2024
Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models
Matteo Tomasetto
Andrea Manzoni
Francesco Braghin
AI4CE
82
2
0
09 Sep 2024
Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach
Daniel Lengyel
P. Parpas
B. Hamzi
H. Owhadi
90
1
0
12 Aug 2024
Limits and Powers of Koopman Learning
Matthew J. Colbrook
Igor Mezić
Alexei Stepanenko
62
11
0
08 Jul 2024
From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach
Timothée Devergne
Vladimir Kostic
Michele Parrinello
Massimiliano Pontil
67
3
0
13 Jun 2024
Learning the Infinitesimal Generator of Stochastic Diffusion Processes
Vladimir Kostic
Karim Lounici
Helene Halconruy
Timothée Devergne
Massimiliano Pontil
DiffM
62
4
0
21 May 2024
Dynamical systems and complex networks: A Koopman operator perspective
Stefan Klus
Natavsa Djurdjevac Conrad
51
3
0
14 May 2024
Koopman-Assisted Reinforcement Learning
Preston Rozwood
Edward Mehrez
Ludger Paehler
Wen Sun
Steven L. Brunton
107
10
0
04 Mar 2024
On the Convergence of Hermitian Dynamic Mode Decomposition
Nicolas Boullé
Matthew J. Colbrook
71
3
0
06 Jan 2024
Simplicity bias, algorithmic probability, and the random logistic map
B. Hamzi
K. Dingle
61
4
0
31 Dec 2023
Featurizing Koopman Mode Decomposition For Robust Forecasting
D. Aristoff
J. Copperman
Nathan Mankovich
Alexander Davies
55
2
0
14 Dec 2023
Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning
B. Hamzi
Marcus Hutter
H. Owhadi
68
3
0
21 Nov 2023
Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder
Priyam Gupta
Peter J. Schmid
D. Sipp
T. Sayadi
Georgios Rigas
118
5
0
16 Oct 2023
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
Ilan Naiman
N. Benjamin Erichson
Pu Ren
Lbnl Michael W. Mahoney ICSI
Omri Azencot
AI4TS
90
26
0
04 Oct 2023
Neural Koopman prior for data assimilation
Anthony Frion
Lucas Drumetz
M. Dalla Mura
Guillaume Tochon
Abdeldjalil Aissa El Bey
AI4TS
AI4CE
66
5
0
11 Sep 2023
Online Infinite-Dimensional Regression: Learning Linear Operators
Vinod Raman
Unique Subedi
Ambuj Tewari
51
0
0
08 Sep 2023
Transfer operators on graphs: Spectral clustering and beyond
Stefan Klus
Maia Trower
63
5
0
19 May 2023
Pseudo-Hamiltonian system identification
Sigurd Holmsen
Sølve Eidnes
S. Riemer-Sørensen
111
4
0
09 May 2023
Reservoir Computing with Error Correction: Long-term Behaviors of Stochastic Dynamical Systems
Cheng Fang
Yubin Lu
Ting Gao
Jinqiao Duan
50
4
0
01 May 2023
Controlled density transport using Perron Frobenius generators
Jake Buzhardt
Phanindra Tallapragada
OT
34
3
0
26 Apr 2023
Auxiliary Functions as Koopman Observables: Data-Driven Analysis of Dynamical Systems via Polynomial Optimization
J. Bramburger
Giovanni Fantuzzi
67
10
0
02 Mar 2023
Kernelized Diffusion maps
Loucas Pillaud-Vivien
Francis R. Bach
68
7
0
13 Feb 2023
Learning Dynamical Systems from Data: A Simple Cross-Validation Perspective, Part V: Sparse Kernel Flows for 132 Chaotic Dynamical Systems
L. Yang
Xiuwen Sun
B. Hamzi
H. Owhadi
Nai-ming Xie
91
20
0
24 Jan 2023
Koopman Operators for Modeling and Control of Soft Robotics
Lu Shi
Zhichao Liu
Konstantinos Karydis
101
20
0
23 Jan 2023
Likelihood-based generalization of Markov parameter estimation and multiple shooting objectives in system identification
Nicholas Galioto
Alex Arkady Gorodetsky
146
1
0
20 Dec 2022
Safe and Stable Control Synthesis for Uncertain System Models via Distributionally Robust Optimization
Kehan Long
Yinzhuang Yi
Jorge Cortés
Nikolay Atanasov
86
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
111
27
0
24 Sep 2022
Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories
Samuel E. Otto
Sebastian Peitz
C. Rowley
82
19
0
20 Sep 2022
Quantum Mechanics for Closure of Dynamical Systems
D. Freeman
D. Giannakis
J. Slawinska
75
4
0
05 Aug 2022
Ensemble forecasts in reproducing kernel Hilbert space family
Benjamin Dufée
Berenger Hug
É. Mémin
G. Tissot
138
1
0
29 Jul 2022
Residual Dynamic Mode Decomposition: Robust and verified Koopmanism
Matthew J. Colbrook
Lorna J. Ayton
Máté Szőke
71
62
0
19 May 2022
Koopman Methods for Estimation of Animal Motions over Unknown Submanifolds
Nathan Powell
Bowei Liu
Jia Guo
Sai Tej Parachuri
A. Kurdila
154
0
0
10 Mar 2022
An end-to-end deep learning approach for extracting stochastic dynamical systems with
α
α
α
-stable Lévy noise
Cheng Fang
Yubin Lu
Ting Gao
Jinqiao Duan
93
16
0
31 Jan 2022
Towards Data-driven LQR with Koopmanizing Flows
Petar Bevanda
Maximilian Beier
Shahab Heshmati-alamdari
Stefan Sosnowski
Sandra Hirche
46
4
0
27 Jan 2022
Data-driven modelling of nonlinear dynamics by barycentric coordinates and memory
Niklas Wulkow
P. Koltai
V. Sunkara
Christof Schütte
65
3
0
13 Dec 2021
Rigorous data-driven computation of spectral properties of Koopman operators for dynamical systems
Matthew J. Colbrook
Alex Townsend
95
72
0
29 Nov 2021
Learning dynamical systems from data: A simple cross-validation perspective, part III: Irregularly-Sampled Time Series
Jonghyeon Lee
E. Brouwer
B. Hamzi
H. Owhadi
AI4TS
83
19
0
25 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
93
107
0
28 Oct 2021
Learning the Koopman Eigendecomposition: A Diffeomorphic Approach
Petar Bevanda
Johannes Kirmayr
Stefan Sosnowski
Sandra Hirche
114
9
0
15 Oct 2021
Extracting stochastic dynamical systems with
α
α
α
-stable Lévy noise from data
Yang Li
Yubin Lu
Shengyuan Xu
Jinqiao Duan
63
15
0
30 Sep 2021
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