Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models

12 February 2021

Papers citing "Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models"

7 / 7 papers shown

Title
Prof. Robot: Differentiable Robot Rendering Without Static and Self-Collisions Quanyuan Ruan Jiabao Lei Wenhao Yuan Y. Zhang Dekun Lu Guiliang Liu Kui Jia 59 0 0 14 Mar 2025
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics Katharina Friedl Noémie Jaquier Jens Lundell Tamim Asfour Danica Kragic AI4CE 21 0 0 24 Oct 2024
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 19 21 0 10 Nov 2022
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 112 364 0 10 Mar 2020
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 126 219 0 29 Sep 2019
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 226 438 0 01 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 252 1,394 0 01 Dec 2016