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2012.03133
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Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks
IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020
5 December 2020
Pengzhan Jin
Zhen Zhang
Ioannis G. Kevrekidis
George Karniadakis
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Papers citing
"Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks"
30 / 30 papers shown
Neural non-canonical Hamiltonian dynamics for long-time simulations
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Emmanuel Franck
Michael Kraus
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157
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Time-adaptive SympNets for separable Hamiltonian systems
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P. Benner
145
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19 Sep 2025
Variational Neural Networks for Observable Thermodynamics (V-NOTS)
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François Gay-Balmaz
V. Putkaradze
PINN
182
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11 Sep 2025
Stable Port-Hamiltonian Neural Networks
Fabian J. Roth
Dominik K. Klein
Maximilian Kannapinn
Jan Peters
Oliver Weeger
471
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0
04 Feb 2025
Poisson-Dirac Neural Networks for Modeling Coupled Dynamical Systems across Domains
International Conference on Learning Representations (ICLR), 2024
Razmik Arman Khosrovian
Takaharu Yaguchi
Hiroaki Yoshimura
Takashi Matsubara
AI4CE
233
0
0
15 Oct 2024
Symplectic Neural Networks Based on Dynamical Systems
Benjamin K Tapley
295
4
0
19 Aug 2024
Designing Poisson Integrators Through Machine Learning
M. Vaquero
David Martín de Diego
Jorge Cortés
AI4CE
95
3
0
29 Mar 2024
Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs
Yusuke Tanaka
Takaharu Yaguchi
Tomoharu Iwata
N. Ueda
AI4CE
386
0
0
14 Feb 2024
Symmetry Preservation in Hamiltonian Systems: Simulation and Learning
Journal of nonlinear science (J. Nonlinear Sci.), 2023
M. Vaquero
Jorge Cortés
David Martín de Diego
205
8
0
30 Aug 2023
Lie-Poisson Neural Networks (LPNets): Data-Based Computing of Hamiltonian Systems with Symmetries
Neural Networks (Neural Netw.), 2023
Christopher Eldred
François Gay-Balmaz
Sofiia Huraka
V. Putkaradze
204
12
0
29 Aug 2023
Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics
P. Goyal
Süleyman Yıldız
P. Benner
194
5
0
26 Aug 2023
Constructing Custom Thermodynamics Using Deep Learning
Nature Computational Science (Nat. Comput. Sci.), 2023
Xiaoli Chen
Beatrice W. Soh
Z. Ooi
E. Vissol-Gaudin
Haijun Yu
K. Novoselov
K. Hippalgaonkar
Qianxiao Li
AI4CE
268
16
0
08 Aug 2023
Pseudo-Hamiltonian system identification
Journal of Computational Dynamics (J. Comput. Dyn.), 2023
Sigurd Holmsen
Sølve Eidnes
S. Riemer-Sørensen
347
5
0
09 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations
Journal of Computational Physics (JCP), 2023
Sølve Eidnes
K. Lye
385
13
0
27 Apr 2023
Physics-informed neural networks for solving forward and inverse problems in complex beam systems
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Taniya Kapoor
Hongrui Wang
A. Núñez
R. Dollevoet
AI4CE
PINN
279
83
0
02 Mar 2023
Physically Consistent Neural ODEs for Learning Multi-Physics Systems
M. Zakwan
L. D. Natale
B. Svetozarevic
Philipp Heer
Colin N. Jones
Giancarlo Ferrari-Trecate
PINN
AI4CE
244
8
0
11 Nov 2022
FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities
International Conference on Learning Representations (ICLR), 2022
Takashi Matsubara
Takaharu Yaguchi
PINN
250
10
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01 Oct 2022
Constants of motion network
Neural Information Processing Systems (NeurIPS), 2022
M. F. Kasim
Yi Heng Lim
290
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22 Aug 2022
Unifying physical systems' inductive biases in neural ODE using dynamics constraints
Yi Heng Lim
M. F. Kasim
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AI4CE
143
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03 Aug 2022
ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias
International Conference on Machine Learning (ICML), 2022
Yupu Lu
Shi-Min Lin
Guanqi Chen
Jia Pan
245
9
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24 Jun 2022
Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces
Sølve Eidnes
Alexander J. Stasik
Camilla Sterud
Eivind Bøhn
S. Riemer-Sørensen
352
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06 Jun 2022
SympOCnet: Solving optimal control problems with applications to high-dimensional multi-agent path planning problems
SIAM Journal on Scientific Computing (SISC), 2022
Tingwei Meng
Zhen Zhang
Jérome Darbon
George Karniadakis
182
19
0
14 Jan 2022
Locally-symplectic neural networks for learning volume-preserving dynamics
J. Bajārs
186
12
0
19 Sep 2021
GFINNs: GENERIC Formalism Informed Neural Networks for Deterministic and Stochastic Dynamical Systems
Zhen Zhang
Yeonjong Shin
George Karniadakis
AI4CE
223
65
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31 Aug 2021
Physics perception in sloshing scenes with guaranteed thermodynamic consistency
B. Moya
Alberto Badías
D. González
Francisco Chinesta
Elías Cueto
244
17
0
24 Jun 2021
Approximation capabilities of measure-preserving neural networks
Neural Networks (NN), 2021
Aiqing Zhu
Pengzhan Jin
Yifa Tang
276
9
0
21 Jun 2021
Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learning
Chaos (Chaos), 2021
Felix Dietrich
Alexei Makeev
George A. Kevrekidis
N. Evangelou
Tom S. Bertalan
Sebastian Reich
Ioannis G. Kevrekidis
DiffM
300
55
0
10 Jun 2021
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs
MCSS. Mathematics of Control, Signals and Systems (MCSS), 2021
Jérome Darbon
P. Dower
Tingwei Meng
279
29
0
07 May 2021
KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-Zero Training Loss
AAAI Conference on Artificial Intelligence (AAAI), 2021
Yu-Hsueh Chen
Takashi Matsubara
Takaharu Yaguchi
112
5
0
22 Feb 2021
Deep learning of thermodynamics-aware reduced-order models from data
Quercus Hernandez
Alberto Badías
D. González
Francisco Chinesta
Elías Cueto
PINN
AI4CE
226
88
0
03 Jul 2020
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