Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2201.10085
Cited By
v1
v2 (latest)
Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately
25 January 2022
A. Sosanya
S. Greydanus
PINN
AI4CE
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately"
19 / 19 papers shown
Mass Conservation on Rails - Rethinking Physics-Informed Learning of Ice Flow Vector Fields
Kim Bente
Román Marchant
F. Ramos
PINN
AI4CE
144
0
0
07 Oct 2025
Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data
Luke McLennan
Yi Wang
Ryan Farell
Minh Nguyen
Chandrajit Bajaj
97
0
0
08 Sep 2025
Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems
Quercus Hernandez
Max Win
Thomas C. O'Connor
Paulo E. Arratia
Nathaniel Trask
AI4CE
228
1
0
18 Aug 2025
Hamiltonian Neural PDE Solvers through Functional Approximation
Anthony Zhou
Amir Barati Farimani
AI4CE
250
0
0
19 May 2025
MetaSym: A Symplectic Meta-learning Framework for Physical Intelligence
Pranav Vaidhyanathan
Aristotelis Papatheodorou
Mark T. Mitchison
Natalia Ares
Ioannis Havoutis
PINN
AI4CE
376
3
0
23 Feb 2025
Dynami-CAL GraphNet: A Physics-Informed Graph Neural Network Conserving Linear and Angular Momentum for Dynamical Systems
Vinay Sharma
Olga Fink
AI4CE
260
6
0
13 Jan 2025
Lagrangian Neural Networks for Reversible Dissipative Evolution
V. Sundararaghavan
Megna N. Shah
Jeff P. Simmons
PINN
194
1
0
23 May 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
Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure
International Joint Conference on Artificial Intelligence (IJCAI), 2024
Haoyu Chu
Yuto Miyatake
Wenjun Cui
Shikui Wei
Daisuke Furihata
PINN
220
5
0
10 Jan 2024
Discussing the Spectrum of Physics-Enhanced Machine Learning; a Survey on Structural Mechanics Applications
Data-Centric Engineering (DCE), 2023
M. Haywood-Alexander
Wei Liu
Kiran Bacsa
Zhilu Lai
Eleni Chatzi
AI4CE
367
26
0
31 Oct 2023
Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models
IFAC-PapersOnLine (IFAC-PapersOnLine), 2023
Sarvin Moradi
N. Jaensson
Roland Tóth
Maarten Schoukens
PINN
221
9
0
02 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
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
International Conference on Machine Learning (ICML), 2023
Renato Berlinghieri
Brian L. Trippe
David R. Burt
Ryan Giordano
K. Srinivasan
Tamay Ozgokmen
Junfei Xia
Tamara Broderick
235
14
0
20 Feb 2023
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian
Oswin So
Gongjie Li
Evangelos A. Theodorou
Molei Tao
AI4CE
210
3
0
30 Sep 2022
Constants of motion network
Neural Information Processing Systems (NeurIPS), 2022
M. F. Kasim
Yi Heng Lim
284
9
0
22 Aug 2022
KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images
Neurocomputing (Neurocomputing), 2022
Rembert Daems
Jeroen Taets
Francis Wyffels
Guillaume Crevecoeur
228
1
0
22 Jun 2022
Neural Implicit Representations for Physical Parameter Inference from a Single Video
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
Florian Hofherr
Lukas Koestler
Florian Bernard
Zorah Lähner
AI4CE
509
17
0
29 Apr 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview
Zhijie Chen
Mingquan Feng
Junchi Yan
H. Zha
AI4CE
210
17
0
28 Feb 2022
Dissipative Deep Neural Dynamical Systems
Ján Drgoňa
Soumya Vasisht
Aaron Tuor
D. Vrabie
327
13
0
26 Nov 2020
1
Page 1 of 1
