Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks

5 December 2020

Papers citing "Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks"

9 / 9 papers shown

Title
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 23 10 0 27 Apr 2023
Physics-informed neural networks for solving forward and inverse problems in complex beam systems Taniya Kapoor Hongrui Wang A. Núñez R. Dollevoet AI4CE PINN 23 46 0 02 Mar 2023
Constants of motion network M. F. Kasim Yi Heng Lim 34 4 0 22 Aug 2022
SympOCnet: Solving optimal control problems with applications to high-dimensional multi-agent path planning problems Tingwei Meng Zhen Zhang Jérome Darbon George Karniadakis 16 15 0 14 Jan 2022
Locally-symplectic neural networks for learning volume-preserving dynamics J. Bajārs 34 9 0 19 Sep 2021
Approximation capabilities of measure-preserving neural networks Aiqing Zhu Pengzhan Jin Yifa Tang 21 8 0 21 Jun 2021
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs Jérome Darbon P. Dower Tingwei Meng 8 22 0 07 May 2021
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 133 424 0 10 Mar 2020
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 149 220 0 29 Sep 2019