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"

33 / 33 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 95 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 76 0 0 24 Oct 2024
Fast and Feature-Complete Differentiable Physics for Articulated Rigid Bodies with Contact Keenon Werling Dalton Omens Jeongseok Lee Ionnis Exarchos Chenxi Liu PINN 31 80 0 30 Mar 2021
Learning Contact Dynamics using Physically Structured Neural Networks Andreas Hochlehnert Alexander Terenin Steindór Sæmundsson M. Deisenroth 36 16 0 22 Feb 2021
Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN AI4CE 63 47 0 03 Dec 2020
NeuralSim: Augmenting Differentiable Simulators with Neural Networks Eric Heiden David Millard Erwin Coumans Yizhou Sheng Gaurav Sukhatme 49 138 0 09 Nov 2020
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints Marc Finzi Ke Alexander Wang A. Wilson AI4CE 53 127 0 26 Oct 2020
LagNetViP: A Lagrangian Neural Network for Video Prediction Christine Allen-Blanchette Sushant Veer Anirudha Majumdar Naomi Ehrich Leonard 64 30 0 24 Oct 2020
Neural Ordinary Differential Equations for Intervention Modeling Daehoon Gwak Gyuhyeon Sim Michael Poli Stefano Massaroli Jaegul Choo Edward Choi 39 20 0 16 Oct 2020
Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control Yaofeng Desmond Zhong Naomi Ehrich Leonard DRL AI4CE 32 43 0 03 Jul 2020
Learning Physical Constraints with Neural Projections Shuqi Yang Xingzhe He Bo Zhu 3DV AI4CE 69 26 0 23 Jun 2020
Modeling System Dynamics with Physics-Informed Neural Networks Based on Lagrangian Mechanics Manuel A. Roehrl Thomas Runkler Veronika Brandtstetter Michel Tokic Stefan Obermayer PINN 52 79 0 29 May 2020
Learning to Slide Unknown Objects with Differentiable Physics Simulations Changkyu Song Abdeslam Boularias 137 39 0 11 May 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 163 426 0 10 Mar 2020
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 114 1,065 0 21 Feb 2020
Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN AI4CE 53 79 0 20 Feb 2020
Dissecting Neural ODEs Stefano Massaroli Michael Poli Jinkyoo Park Atsushi Yamashita Hajime Asama 78 200 0 19 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 292 42,038 0 03 Dec 2019
Differentiable Convex Optimization Layers Akshay Agrawal Brandon Amos Shane T. Barratt Stephen P. Boyd Steven Diamond Zico Kolter 81 646 0 28 Oct 2019
DiffTaichi: Differentiable Programming for Physical Simulation Yuanming Hu Luke Anderson Tzu-Mao Li Qi Sun N. Carr Jonathan Ragan-Kelley F. Durand 52 377 0 01 Oct 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 186 223 0 29 Sep 2019
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN 83 270 0 26 Sep 2019
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning M. Lutter Christian Ritter Jan Peters PINN AI4CE 56 374 0 10 Jul 2019
Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems M. Lutter Kim D. Listmann Jan Peters PINN 49 71 0 10 Jul 2019
DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions Zhenjia Xu Jiajun Wu Andy Zeng J. Tenenbaum Shuran Song AI4CE 45 111 0 10 Jun 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 67 876 0 04 Jun 2019
Neural Jump Stochastic Differential Equations Junteng Jia Austin R. Benson BDL 47 222 0 24 May 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 244 5,024 0 19 Jun 2018
Data-Augmented Contact Model for Rigid Body Simulation Yifeng Jiang Jiazheng Sun Chenxi Liu PINN 45 21 0 11 Mar 2018
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 335 439 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 461 1,405 0 01 Dec 2016
A Differentiable Physics Engine for Deep Learning in Robotics Jonas Degrave Michiel Hermans J. Dambre Francis Wyffels PINN AI4CE 57 227 0 05 Nov 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 972 149,474 0 22 Dec 2014