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Kernel-based approximation of the Koopman generator and Schrödinger
  operator
v1v2v3 (latest)

Kernel-based approximation of the Koopman generator and Schrödinger operator

27 May 2020
Stefan Klus
Feliks Nuske
B. Hamzi
ArXiv (abs)PDFHTML

Papers citing "Kernel-based approximation of the Koopman generator and Schrödinger operator"

22 / 22 papers shown
Title
Kernel Dynamic Mode Decomposition For Sparse Reconstruction of Closable Koopman Operators
Kernel Dynamic Mode Decomposition For Sparse Reconstruction of Closable Koopman Operators
Nishant Panda
Himanshu Singh
J. Nathan Kutz
97
0
0
11 May 2025
Kernel Methods for the Approximation of the Eigenfunctions of the
  Koopman Operator
Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator
Jonghyeon Lee
B. Hamzi
Boya Hou
H. Owhadi
G. Santin
Umesh Vaidya
144
1
0
21 Dec 2024
Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical
  Systems from Data: A global optimization approach
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
97
1
0
12 Aug 2024
Dynamical systems and complex networks: A Koopman operator perspective
Dynamical systems and complex networks: A Koopman operator perspective
Stefan Klus
Natavsa Djurdjevac Conrad
51
3
0
14 May 2024
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
Edoardo Caldarelli
Antoine Chatalic
Adrià Colomé
C. Molinari
C. Ocampo‐Martinez
Carme Torras
Lorenzo Rosasco
105
0
0
05 Mar 2024
Simplicity bias, algorithmic probability, and the random logistic map
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
Featurizing Koopman Mode Decomposition For Robust Forecasting
D. Aristoff
J. Copperman
Nathan Mankovich
Alexander Davies
63
2
0
14 Dec 2023
Bridging Algorithmic Information Theory and Machine Learning: A New
  Approach to Kernel Learning
Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning
B. Hamzi
Marcus Hutter
H. Owhadi
83
3
0
21 Nov 2023
Learning invariant representations of time-homogeneous stochastic
  dynamical systems
Learning invariant representations of time-homogeneous stochastic dynamical systems
Vladimir Kostic
P. Novelli
Riccardo Grazzi
Karim Lounici
Massimiliano Pontil
70
8
0
19 Jul 2023
Learning Dynamical Systems from Data: A Simple Cross-Validation
  Perspective, Part V: Sparse Kernel Flows for 132 Chaotic Dynamical Systems
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
One-Shot Learning of Stochastic Differential Equations with Data Adapted
  Kernels
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
Ensemble forecasts in reproducing kernel Hilbert space family
Ensemble forecasts in reproducing kernel Hilbert space family
Benjamin Dufée
Berenger Hug
É. Mémin
G. Tissot
138
1
0
29 Jul 2022
Learning dynamical systems from data: A simple cross-validation
  perspective, part III: Irregularly-Sampled Time Series
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
Learning to Forecast Dynamical Systems from Streaming Data
Learning to Forecast Dynamical Systems from Streaming Data
D. Giannakis
Amelia Henriksen
J. Tropp
Rachel A. Ward
AI4TS
67
17
0
20 Sep 2021
Learning and Leveraging Features in Flow-Like Environments to Improve
  Situational Awareness
Learning and Leveraging Features in Flow-Like Environments to Improve Situational Awareness
Tahiya Salam
Victoria Edwards
M. A. Hsieh
49
7
0
13 Sep 2021
Symmetric and antisymmetric kernels for machine learning problems in
  quantum physics and chemistry
Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry
Stefan Klus
Patrick Gelß
Feliks Nuske
Frank Noé
47
21
0
31 Mar 2021
Modern Koopman Theory for Dynamical Systems
Modern Koopman Theory for Dynamical Systems
Steven L. Brunton
M. Budišić
E. Kaiser
J. Nathan Kutz
AI4CE
156
423
0
24 Feb 2021
On the Universal Transformation of Data-Driven Models to Control Systems
On the Universal Transformation of Data-Driven Models to Control Systems
Sebastian Peitz
Katharina Bieker
AI4CE
40
11
0
09 Feb 2021
Kernel methods for center manifold approximation and a data-based
  version of the Center Manifold Theorem
Kernel methods for center manifold approximation and a data-based version of the Center Manifold Theorem
B. Haasdonk
B. Hamzi
G. Santin
D. Wittwar
83
21
0
01 Dec 2020
Overcoming the curse of dimensionality with Laplacian regularization in
  semi-supervised learning
Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning
Vivien A. Cabannes
Loucas Pillaud-Vivien
Francis R. Bach
Alessandro Rudi
80
19
0
09 Sep 2020
Learning dynamical systems from data: a simple cross-validation
  perspective
Learning dynamical systems from data: a simple cross-validation perspective
B. Hamzi
H. Owhadi
78
41
0
09 Jul 2020
Tensor-based computation of metastable and coherent sets
Tensor-based computation of metastable and coherent sets
Feliks Nuske
Patrick Gelß
Stefan Klus
C. Clementi
32
13
0
12 Aug 2019
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