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2107.08024
Cited By
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems
Physical Review E (PRE), 2021
16 July 2021
Shaan Desai
M. Mattheakis
David Sondak
P. Protopapas
Stephen J. Roberts
AI4CE
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Papers citing
"Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems"
41 / 41 papers shown
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On the Generalization of Data-Assisted Control in port-Hamiltonian Systems (DAC-pH)
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Rapid training of Hamiltonian graph networks using random features
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Stable Port-Hamiltonian Neural Networks
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Learning Subsystem Dynamics in Nonlinear Systems via Port-Hamiltonian Neural Networks
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Human-Robot Cooperative Distribution Coupling for Hamiltonian-Constrained Social Navigation
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Chao Yu
Yu Wang
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Data-driven identification of latent port-Hamiltonian systems
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Jonas Kneifl
Julius Herb
Patrick Buchfink
Jörg Fehr
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Physics-Constrained Learning for PDE Systems with Uncertainty Quantified Port-Hamiltonian Models
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Separable Hamiltonian Neural Networks
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315
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Reversible and irreversible bracket-based dynamics for deep graph neural networks
Neural Information Processing Systems (NeurIPS), 2023
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Kookjin Lee
N. Trask
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316
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Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification
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Tom Z. Jiahao
George J. Pappas
235
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15 May 2023
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior
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Thomas Beckers
Jacob H. Seidman
P. Perdikaris
George J. Pappas
PINN
268
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15 May 2023
Pseudo-Hamiltonian system identification
Journal of Computational Dynamics (J. Comput. Dyn.), 2023
Sigurd Holmsen
Sølve Eidnes
S. Riemer-Sørensen
388
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09 May 2023
Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models
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Roland Tóth
Maarten Schoukens
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276
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Pseudo-Hamiltonian neural networks for learning partial differential equations
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437
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Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks
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Ufuk Topcu
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311
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Francisco Chinesta
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390
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Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces
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Learning reversible symplectic dynamics
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Victoria G Klein
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148
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Thermodynamics-informed graph neural networks
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Alberto Badías
Francisco Chinesta
Elías Cueto
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310
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Deconstructing the Inductive Biases of Hamiltonian Neural Networks
International Conference on Learning Representations (ICLR), 2022
Nate Gruver
Marc Finzi
Samuel Stanton
A. Wilson
AI4CE
265
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Noether Networks: Meta-Learning Useful Conserved Quantities
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Ferran Alet
Dylan D. Doblar
Allan Zhou
J. Tenenbaum
Kenji Kawaguchi
Chelsea Finn
279
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One-Shot Transfer Learning of Physics-Informed Neural Networks
Shaan Desai
M. Mattheakis
H. Joy
P. Protopapas
Stephen J. Roberts
PINN
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390
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Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling
Kookjin Lee
Nathaniel Trask
P. Stinis
244
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0
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Hamiltonian neural networks for solving equations of motion
Physical Review E (PRE), 2020
M. Mattheakis
David Sondak
Akshunna S. Dogra
P. Protopapas
632
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0
29 Jan 2020
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