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Symplectic Gaussian Process Regression of Hamiltonian Flow Maps

Symplectic Gaussian Process Regression of Hamiltonian Flow Maps

K. Rath
C. Albert
B. Bischl
U. Toussaint
ArXiv (abs)PDFHTML

Papers citing "Symplectic Gaussian Process Regression of Hamiltonian Flow Maps"

13 / 13 papers shown
Title
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
Peter Zaspel
Michael Günther
56
2
0
26 Jun 2024
Learning Hamiltonian Dynamics with Reproducing Kernel Hilbert Spaces and Random Features
Learning Hamiltonian Dynamics with Reproducing Kernel Hilbert Spaces and Random Features
Torbjorn Smith
Olav Egeland
39
2
0
11 Apr 2024
Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs
Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs
Yusuke Tanaka
Takaharu Yaguchi
Tomoharu Iwata
N. Ueda
AI4CE
116
0
0
14 Feb 2024
Exact Inference for Continuous-Time Gaussian Process Dynamics
Exact Inference for Continuous-Time Gaussian Process Dynamics
K. Ensinger
Nicholas Tagliapietra
Sebastian Ziesche
Sebastian Trimpe
56
1
0
05 Sep 2023
Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification
Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification
Thomas Beckers
Tom Z. Jiahao
George J. Pappas
78
3
0
15 May 2023
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior
Thomas Beckers
Jacob H. Seidman
P. Perdikaris
George J. Pappas
PINN
85
17
0
15 May 2023
Learning Energy Conserving Dynamics Efficiently with Hamiltonian Gaussian Processes
Learning Energy Conserving Dynamics Efficiently with Hamiltonian Gaussian Processes
M. Ross
Markus Heinonen
52
2
0
03 Mar 2023
Hamiltonian Neural Networks with Automatic Symmetry Detection
Hamiltonian Neural Networks with Automatic Symmetry Detection
Eva Dierkes
Christian Offen
Sina Ober-Blobaum
K. Flaßkamp
96
9
0
19 Jan 2023
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems
Valentin Duruisseaux
T. Duong
Melvin Leok
Nikolay Atanasov
DRLAI4CE
116
13
0
29 Nov 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks
Valentin Duruisseaux
J. Burby
Q. Tang
88
11
0
11 Oct 2022
Physically Consistent Learning of Conservative Lagrangian Systems with Gaussian Processes
Physically Consistent Learning of Conservative Lagrangian Systems with Gaussian Processes
G. Evangelisti
Sandra Hirche
60
15
0
24 Jun 2022
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision
I. Higgins
Peter Wirnsberger
Andrew Jaegle
Aleksandar Botev
89
8
0
10 Nov 2021
Structure-preserving Gaussian Process Dynamics
Structure-preserving Gaussian Process Dynamics
K. Ensinger
Friedrich Solowjow
Sebastian Ziesche
Michael Tiemann
Sebastian Trimpe
73
9
0
02 Feb 2021