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Learning to Accelerate Partial Differential Equations via Latent Global Evolution

15 June 2022

Papers citing "Learning to Accelerate Partial Differential Equations via Latent Global Evolution"

22 / 22 papers shown

Title
Learning to Solve PDE-constrained Inverse Problems with Graph Networks Qingqing Zhao David B. Lindell Gordon Wetzstein AI4CE 80 40 0 01 Jun 2022
Physical Design using Differentiable Learned Simulators Kelsey R. Allen Tatiana López-Guevara Kimberly L. Stachenfeld Alvaro Sanchez-Gonzalez Peter W. Battaglia Jessica B. Hamrick Tobias Pfaff AI4CE 93 44 0 01 Feb 2022
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 500 2,444 0 18 Oct 2020
Learning Mesh-Based Simulation with Graph Networks Tobias Pfaff Meire Fortunato Alvaro Sanchez-Gonzalez Peter W. Battaglia AI4CE 82 790 0 07 Oct 2020
Implicit Rank-Minimizing Autoencoder Li Jing Jure Zbontar Yann LeCun SSL DRL 70 48 0 01 Oct 2020
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers Kiwon Um R. Brand Yun Fei Fei Philipp Holl N. Thürey AI4CE 54 271 0 30 Jun 2020
Symbolic Pregression: Discovering Physical Laws from Distorted Video S. Udrescu Max Tegmark 63 41 0 19 May 2020
Neural Operator: Graph Kernel Network for Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar 199 748 0 07 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 141 1,101 0 21 Feb 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,150 0 08 Oct 2019
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems Meng Tang Yimin Liu L. Durlofsky AI4CE 60 261 0 16 Aug 2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model Alex X. Lee Anusha Nagabandi Pieter Abbeel Sergey Levine OffRL BDL 85 382 0 01 Jul 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning Carles Gelada Saurabh Kumar Jacob Buckman Ofir Nachum Marc G. Bellemare BDL 81 288 0 06 Jun 2019
Learning Latent Dynamics for Planning from Pixels Danijar Hafner Timothy Lillicrap Ian S. Fischer Ruben Villegas David R Ha Honglak Lee James Davidson BDL 88 1,446 0 12 Nov 2018
Group Normalization Yuxin Wu Kaiming He 231 3,669 0 22 Mar 2018
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions Sjoerd van Steenkiste Michael Chang Klaus Greff Jürgen Schmidhuber BDL OCL DRL 206 291 0 28 Feb 2018
Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow S. Wiewel M. Becher N. Thürey AI4CE 86 276 0 27 Feb 2018
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification Yinhao Zhu N. Zabaras UQCV BDL 111 645 0 21 Jan 2018
Visual Interaction Networks Nicholas Watters Andrea Tacchetti T. Weber Razvan Pascanu Peter W. Battaglia Daniel Zoran PINN 3DH 96 279 0 05 Jun 2017
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 333 8,169 0 13 Aug 2016
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter 300 5,532 0 23 Nov 2015
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford Luke Metz Soumith Chintala GAN OOD 266 14,018 0 19 Nov 2015