Symplectic Learning for Hamiltonian Neural Networks

22 June 2021

Papers citing "Symplectic Learning for Hamiltonian Neural Networks"

10 / 10 papers shown

Title
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling Nicholas Galioto Harsh Sharma Boris Kramer Alex Arkady Gorodetsky 38 0 0 23 Jan 2024
Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators Haakon Noren Sølve Eidnes E. Celledoni 21 3 0 06 Jun 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 18 10 0 27 Apr 2023
Learning Hamiltonian Systems with Mono-Implicit Runge-Kutta Methods Haakon Noren 21 3 0 07 Mar 2023
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems Valentin Duruisseaux T. Duong Melvin Leok Nikolay A. Atanasov DRL AI4CE 18 12 0 29 Nov 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks Valentin Duruisseaux J. Burby Q. Tang 30 11 0 11 Oct 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
Learning Hamiltonians of constrained mechanical systems E. Celledoni A. Leone Davide Murari B. Owren AI4CE 41 17 0 31 Jan 2022
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 130 424 0 10 Mar 2020
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 146 219 0 29 Sep 2019