Deconstructing the Inductive Biases of Hamiltonian Neural Networks

10 February 2022

Papers citing "Deconstructing the Inductive Biases of Hamiltonian Neural Networks"

31 / 31 papers shown

Title
23 DoF Grasping Policies from a Raw Point Cloud Martin Matak Karl Van Wyk Tucker Hermans 3DPC 85 0 0 21 Nov 2024
Poisson-Dirac Neural Networks for Modeling Coupled Dynamical Systems across Domains Razmik Arman Khosrovian Takaharu Yaguchi Hiroaki Yoshimura Takashi Matsubara AI4CE 27 0 0 15 Oct 2024
Geometric Fabrics: a Safe Guiding Medium for Policy Learning Karl Van Wyk Ankur Handa Viktor Makoviychuk Yijie Guo Arthur Allshire Nathan D. Ratliff 27 5 0 03 May 2024
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs Yogesh Verma Markus Heinonen Vikas K. Garg AI4CE 33 26 0 15 Apr 2024
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning Zi-Yu Khoo Jonathan Sze Choong Low Stéphane Bressan ELM 26 0 0 15 Dec 2023
Symmetry-invariant quantum machine learning force fields Isabel Nha Minh Le Oriel Kiss Julian Schuhmacher I. Tavernelli F. Tacchino AI4CE 28 12 0 19 Nov 2023
A Bayesian framework for discovering interpretable Lagrangian of dynamical systems from data Tapas Tripura Souvik Chakraborty 31 3 0 10 Oct 2023
Separable Hamiltonian Neural Networks Zi-Yu Khoo Dawen Wu Jonathan Sze Choong Low Stéphane Bressan 22 1 0 03 Sep 2023
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases Yang Liu Jiashun Cheng Haihong Zhao Tingyang Xu P. Zhao Fugee Tsung Jia Li Yu Rong AI4CE 40 18 0 25 Aug 2023
Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks S. Bishnoi Ravinder Bhattoo J. Jayadeva Sayan Ranu N. M. A. Krishnan PINN AI4CE 34 1 0 11 Jul 2023
Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics S. Bishnoi J. Jayadeva Sayan Ranu N. M. A. Krishnan 24 3 0 20 Jun 2023
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints Alistair J R White Niki Kilbertus Maximilian Gelbrecht Niklas Boers 20 6 0 16 Jun 2023
Reversible and irreversible bracket-based dynamics for deep graph neural networks A. Gruber Kookjin Lee N. Trask AI4CE 25 9 0 24 May 2023
Learning Energy Conserving Dynamics Efficiently with Hamiltonian Gaussian Processes M. Ross Markus Heinonen 18 2 0 03 Mar 2023
Discovering interpretable Lagrangian of dynamical systems from data Tapas Tripura S. Chakraborty 27 3 0 09 Feb 2023
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning Yeongwoo Song Hawoong Jeong OOD AI4CE 24 1 0 02 Dec 2022
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems A. Thangamuthu Gunjan Kumar S. Bishnoi Ravinder Bhattoo N. M. A. Krishnan Sayan Ranu AI4CE PINN 37 22 0 10 Nov 2022
Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 27 13 0 03 Nov 2022
Homotopy-based training of NeuralODEs for accurate dynamics discovery Joon-Hyuk Ko Hankyul Koh Nojun Park W. Jhe 43 8 0 04 Oct 2022
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian Oswin So Gongjie Li Evangelos A. Theodorou Molei Tao AI4CE 30 3 0 30 Sep 2022
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 31 17 0 23 Sep 2022
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems S. Bishnoi Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 32 19 0 22 Sep 2022
Learning the Dynamics of Particle-based Systems with Lagrangian Graph Neural Networks Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan PINN AI4CE 36 20 0 03 Sep 2022
Unifying physical systems' inductive biases in neural ODE using dynamics constraints Yi Heng Lim M. F. Kasim PINN AI4CE 17 5 0 03 Aug 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images Rembert Daems Jeroen Taets Francis Wyffels Guillaume Crevecoeur 21 1 0 22 Jun 2022
Learning Trajectories of Hamiltonian Systems with Neural Networks Katsiaryna Haitsiukevich Alexander Ilin 29 4 0 11 Apr 2022
Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning Ziming Liu Yunyue Chen Yuanqi Du Max Tegmark PINN AI4CE 40 22 0 28 Sep 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 79 185 0 19 Apr 2021
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty 52 34 0 12 Feb 2021
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 146 220 0 29 Sep 2019