Neural non-canonical Hamiltonian dynamics for long-time simulations
Fuente:
arXiv
Saved in:
| Main Authors: | Courtès, Clémentine, Franck, Emmanuel, Kraus, Michael, Navoret, Laurent, Trémant, Léopold |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hamiltonian reduction using a convolutional auto-encoder coupled to an Hamiltonian neural network
by: Côte, Raphaël, et al.
Published: (2023)
by: Côte, Raphaël, et al.
Published: (2023)
Reduced Particle in Cell method for the Vlasov-Poisson system using auto-encoder and Hamiltonian neural
by: Franck, Emmanuel, et al.
Published: (2025)
by: Franck, Emmanuel, et al.
Published: (2025)
From flocking to jamming in collective cell dynamics: a Vicsek-like model including contact forces
by: Navoret, Laurent, et al.
Published: (2025)
by: Navoret, Laurent, et al.
Published: (2025)
Approximately well-balanced Discontinuous Galerkin methods using bases enriched with Physics-Informed Neural Networks
by: Franck, Emmanuel, et al.
Published: (2023)
by: Franck, Emmanuel, et al.
Published: (2023)
Micromagnetic simulations of the size dependence of the Curie temperature in ferromagnetic nanowires and nanolayers
by: Courtès, Clémentine, et al.
Published: (2024)
by: Courtès, Clémentine, et al.
Published: (2024)
Fourth-order entropy-stable lattice Boltzmann schemes for hyperbolic systems
by: Bellotti, Thomas, et al.
Published: (2024)
by: Bellotti, Thomas, et al.
Published: (2024)
Neural semi-Lagrangian method for high-dimensional advection-diffusion problems
by: Franck, Emmanuel, et al.
Published: (2025)
by: Franck, Emmanuel, et al.
Published: (2025)
Hamiltonian Matching for Symplectic Neural Integrators
by: Canizares, Priscilla, et al.
Published: (2024)
by: Canizares, Priscilla, et al.
Published: (2024)
Generalizing the SINDy approach with nested neural networks
by: Fiorini, Camilla, et al.
Published: (2024)
by: Fiorini, Camilla, et al.
Published: (2024)
Solving and learning advective multiscale Darcian dynamics with the Neural Basis Method
by: Wang, Yuhe, et al.
Published: (2026)
by: Wang, Yuhe, et al.
Published: (2026)
Training Hamiltonian neural networks without backpropagation
by: Rahma, Atamert, et al.
Published: (2024)
by: Rahma, Atamert, et al.
Published: (2024)
Numerical simulation of transient heat conduction with moving heat source using Physics Informed Neural Networks
by: Kalyan, Anirudh, et al.
Published: (2025)
by: Kalyan, Anirudh, et al.
Published: (2025)
Long-time Integration of Nonlinear Wave Equations with Neural Operators
by: Lei, Guanhang, et al.
Published: (2024)
by: Lei, Guanhang, et al.
Published: (2024)
Parareal Neural Networks Emulating a Parallel-in-time Algorithm
by: Lee, Chang-Ock, et al.
Published: (2021)
by: Lee, Chang-Ock, et al.
Published: (2021)
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
by: Lingsch, Levi, et al.
Published: (2023)
by: Lingsch, Levi, et al.
Published: (2023)
Pseudo-Hamiltonian neural networks for learning partial differential equations
by: Eidnes, Sølve, et al.
Published: (2023)
by: Eidnes, Sølve, et al.
Published: (2023)
Data-Augmented Predictive Deep Neural Network: Enhancing the extrapolation capabilities of non-intrusive surrogate models
by: Sun, Shuwen, et al.
Published: (2024)
by: Sun, Shuwen, et al.
Published: (2024)
The Proof of Kolmogorov-Arnold May Illuminate Neural Network Learning
by: Freedman, Michael H.
Published: (2024)
by: Freedman, Michael H.
Published: (2024)
Neural Low-Discrepancy Sequences
by: Van Huffel, Michael Etienne, et al.
Published: (2025)
by: Van Huffel, Michael Etienne, et al.
Published: (2025)
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
by: Zaspel, Peter, et al.
Published: (2024)
by: Zaspel, Peter, et al.
Published: (2024)
Neural network-enhanced integrators for simulating ordinary differential equations
by: Othmane, Amine, et al.
Published: (2025)
by: Othmane, Amine, et al.
Published: (2025)
Determinant Estimation under Memory Constraints and Neural Scaling Laws
by: Ameli, Siavash, et al.
Published: (2025)
by: Ameli, Siavash, et al.
Published: (2025)
SVD-PINNs: Transfer Learning of Physics-Informed Neural Networks via Singular Value Decomposition
by: Gao, Yihang, et al.
Published: (2022)
by: Gao, Yihang, et al.
Published: (2022)
Message-Passing Monte Carlo: Generating low-discrepancy point sets via Graph Neural Networks
by: Rusch, T. Konstantin, et al.
Published: (2024)
by: Rusch, T. Konstantin, et al.
Published: (2024)
Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
by: Blechschmidt, Jan, et al.
Published: (2025)
by: Blechschmidt, Jan, et al.
Published: (2025)
On the generalization ability of coarse-grained molecular dynamics models for non-equilibrium processes
by: Lyu, Liyao, et al.
Published: (2024)
by: Lyu, Liyao, et al.
Published: (2024)
Continuum Attention for Neural Operators
by: Calvello, Edoardo, et al.
Published: (2024)
by: Calvello, Edoardo, et al.
Published: (2024)
Multigrade Neural Network Approximation
by: Zhang, Shijun, et al.
Published: (2026)
by: Zhang, Shijun, et al.
Published: (2026)
Energy-preserving integration of non-canonical Hamiltonian systems by continuous-stage methods
by: Tang, Wensheng
Published: (2018)
by: Tang, Wensheng
Published: (2018)
Approximation by non-symmetric networks for cross-domain learning
by: Mhaskar, Hrushikesh
Published: (2023)
by: Mhaskar, Hrushikesh
Published: (2023)
Stable neural networks and connections to continuous dynamical systems
by: Ehrhardt, Matthias J., et al.
Published: (2025)
by: Ehrhardt, Matthias J., et al.
Published: (2025)
On latent dynamics learning in nonlinear reduced order modeling
by: Farenga, Nicola, et al.
Published: (2024)
by: Farenga, Nicola, et al.
Published: (2024)
THINNs: Thermodynamically Informed Neural Networks
by: Castro, Javier, et al.
Published: (2025)
by: Castro, Javier, et al.
Published: (2025)
Preconditioning for Physics-Informed Neural Networks
by: Liu, Songming, et al.
Published: (2024)
by: Liu, Songming, et al.
Published: (2024)
Reconstruction of dynamical systems from data without time labels
by: Zeng, Zhijun, et al.
Published: (2023)
by: Zeng, Zhijun, et al.
Published: (2023)
Sequential decoder training for improved latent space dynamics identification
by: Anderson, William, et al.
Published: (2025)
by: Anderson, William, et al.
Published: (2025)
Graph Neural Regularizers for PDE Inverse Problems
by: Lauga, William, et al.
Published: (2025)
by: Lauga, William, et al.
Published: (2025)
Neural Measures for learning distributions of Random PDEs
by: Arampatzis, Georgios, et al.
Published: (2025)
by: Arampatzis, Georgios, et al.
Published: (2025)
Dual-Balancing for Physics-Informed Neural Networks
by: Zhou, Chenhong, et al.
Published: (2025)
by: Zhou, Chenhong, et al.
Published: (2025)
Physics-Informed Geometry-Aware Neural Operator
by: Zhong, Weiheng, et al.
Published: (2024)
by: Zhong, Weiheng, et al.
Published: (2024)
Similar Items
-
Hamiltonian reduction using a convolutional auto-encoder coupled to an Hamiltonian neural network
by: Côte, Raphaël, et al.
Published: (2023) -
Reduced Particle in Cell method for the Vlasov-Poisson system using auto-encoder and Hamiltonian neural
by: Franck, Emmanuel, et al.
Published: (2025) -
From flocking to jamming in collective cell dynamics: a Vicsek-like model including contact forces
by: Navoret, Laurent, et al.
Published: (2025) -
Approximately well-balanced Discontinuous Galerkin methods using bases enriched with Physics-Informed Neural Networks
by: Franck, Emmanuel, et al.
Published: (2023) -
Micromagnetic simulations of the size dependence of the Curie temperature in ferromagnetic nanowires and nanolayers
by: Courtès, Clémentine, et al.
Published: (2024)