Constraint-based graph network simulator

16 December 2021

Yulia Rubanova

Alvaro Sanchez-Gonzalez

Papers citing "Constraint-based graph network simulator"

31 / 31 papers shown

Title
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications Jiaqi Han Jiacheng Cen Liming Wu Zongzhao Li Xiangzhe Kong ... Zhewei Wei Deli Zhao Yu Rong Wenbing Huang Wenbing Huang AI4CE 104 23 0 01 Mar 2024
Learned Coarse Models for Efficient Turbulence Simulation Kimberly L. Stachenfeld D. Fielding Dmitrii Kochkov M. Cranmer Tobias Pfaff Jonathan Godwin Can Cui S. Ho Peter W. Battaglia Alvaro Sanchez-Gonzalez AI4CE 62 79 0 31 Dec 2021
DC3: A learning method for optimization with hard constraints P. Donti David Rolnick J. Zico Kolter AI4CE 63 189 0 25 Apr 2021
Machine learning accelerated computational fluid dynamics Dmitrii Kochkov Jamie A. Smith Ayya Alieva Qing Wang M. Brenner Stephan Hoyer AI4CE 92 849 0 28 Jan 2021
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints Marc Finzi Ke Alexander Wang A. Wilson AI4CE 59 127 0 26 Oct 2020
Learning Mesh-Based Simulation with Graph Networks Tobias Pfaff Meire Fortunato Alvaro Sanchez-Gonzalez Peter W. Battaglia AI4CE 75 761 0 07 Oct 2020
Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction Filipe de Avila Belbute-Peres T. Economon J. Zico Kolter AI4CE 82 230 0 08 Jul 2020
Learning Physical Constraints with Neural Projections Shuqi Yang Xingzhe He Bo Zhu 3DV AI4CE 69 26 0 23 Jun 2020
Multiscale Deep Equilibrium Models Shaojie Bai V. Koltun J. Zico Kolter BDL 78 212 0 15 Jun 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 165 426 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 123 1,065 0 21 Feb 2020
Towards Physics-informed Deep Learning for Turbulent Flow Prediction Rui Wang K. Kashinath M. Mustafa A. Albert Rose Yu PINN AI4CE 36 361 0 20 Nov 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 198 223 0 29 Sep 2019
Hamiltonian Graph Networks with ODE Integrators Alvaro Sanchez-Gonzalez V. Bapst Kyle Cranmer Peter W. Battaglia AI4CE 81 177 0 27 Sep 2019
Deep Equilibrium Models Shaojie Bai J. Zico Kolter V. Koltun 72 663 0 03 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
Latent ODEs for Irregularly-Sampled Time Series Yulia Rubanova Ricky T. Q. Chen David Duvenaud BDL AI4TS 63 254 0 08 Jul 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 83 876 0 04 Jun 2019
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver Po-Wei Wang P. Donti Bryan Wilder Zico Kolter LRM NAI 67 262 0 29 May 2019
Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows Nils Thuerey Konstantin Weissenow L. Prantl Xiangyu Y. Hu AI4CE 64 380 0 18 Oct 2018
Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids Yunzhu Li Jiajun Wu Russ Tedrake J. Tenenbaum Antonio Torralba PINN AI4CE 67 391 0 03 Oct 2018
Flexible Neural Representation for Physics Prediction Damian Mrowca Chengxu Zhuang E. Wang Nick Haber Li Fei-Fei J. Tenenbaum Daniel L. K. Yamins OCL AI4CE 56 248 0 21 Jun 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 286 5,024 0 19 Jun 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 527 3,101 0 04 Jun 2018
Graph networks as learnable physics engines for inference and control Alvaro Sanchez-Gonzalez N. Heess Jost Tobias Springenberg J. Merel Martin Riedmiller R. Hadsell Peter W. Battaglia GNN AI4CE PINN OCL 166 597 0 04 Jun 2018
Reviving and Improving Recurrent Back-Propagation Renjie Liao Yuwen Xiong Ethan Fetaya Lisa Zhang Kijung Yoon Xaq Pitkow R. Urtasun R. Zemel BDL 63 118 0 16 Mar 2018
Application of Convolutional Neural Network to Predict Airfoil Lift Coefficient Yao Zhang WoongJe Sung D. Mavris 18 221 0 29 Dec 2017
OptNet: Differentiable Optimization as a Layer in Neural Networks Brandon Amos J. Zico Kolter 148 952 0 01 Mar 2017
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 494 1,405 0 01 Dec 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 621 3,264 0 24 Nov 2016
Layer Normalization Jimmy Lei Ba J. Kiros Geoffrey E. Hinton 314 10,412 0 21 Jul 2016