Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

5 November 2018

Papers citing "Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations"

39 / 139 papers shown

Title
Measure-conditional Discriminator with Stationary Optimum for GANs and Statistical Distance Surrogates Liu Yang Tingwei Meng George Karniadakis 30 1 0 17 Jan 2021
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 40 146 0 22 Dec 2020
Deep Autoencoder based Energy Method for the Bending, Vibration, and Buckling Analysis of Kirchhoff Plates X. Zhuang Hongwei Guo N. Alajlan Timon Rabczuk AI4CE 19 311 0 09 Oct 2020
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data Kadierdan Kaheman Steven L. Brunton J. Nathan Kutz 14 83 0 12 Sep 2020
The Seven-League Scheme: Deep learning for large time step Monte Carlo simulations of stochastic differential equations Shuaiqiang Liu L. Grzelak C. Oosterlee 12 11 0 07 Sep 2020
Physics-Informed Neural Networks for Nonhomogeneous Material Identification in Elasticity Imaging Enrui Zhang Minglang Yin George Karniadakis 14 64 0 02 Sep 2020
Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-Informed Deep Generative Models Liu Yang C. Daskalakis George Karniadakis 12 12 0 05 Aug 2020
Adaptive Physics-Informed Neural Networks for Markov-Chain Monte Carlo M. A. Nabian Hadi Meidani 22 6 0 03 Aug 2020
Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models Sergio Botelho Ameya Joshi Biswajit Khara Soumik Sarkar Chinmay Hegde Santi S. Adavani Baskar Ganapathysubramanian AI4CE 24 6 0 24 Jul 2020
Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks Dylan Randle P. Protopapas David Sondak GAN 21 5 0 21 Jul 2020
RODE-Net: Learning Ordinary Differential Equations with Randomness from Data Junyu Liu Zichao Long Ranran Wang Jie Sun Bin Dong 13 9 0 03 Jun 2020
Deep Learning of Dynamic Subsurface Flow via Theory-guided Generative Adversarial Network Tianhao He Dongxiao Zhang AI4CE 27 9 0 02 Jun 2020
Inverse Estimation of Elastic Modulus Using Physics-Informed Generative Adversarial Networks James E. Warner Julian Cuevas Geoffrey F. Bomarito Patrick E. Leser W. Leser GAN 31 10 0 20 May 2020
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization Rishikesh Ranade C. Hill Jay Pathak AI4CE 59 123 0 17 May 2020
Deep Learning Techniques for Inverse Problems in Imaging Greg Ongie A. Jalal Christopher A. Metzler Richard G. Baraniuk A. Dimakis Rebecca Willett 25 521 0 12 May 2020
Physics-constrained indirect supervised learning Yuntian Chen Dongxiao Zhang SSL AI4CE 20 7 0 26 Apr 2020
Bayesian differential programming for robust systems identification under uncertainty Yibo Yang Mohamed Aziz Bhouri P. Perdikaris OOD 33 32 0 15 Apr 2020
Multiresolution Convolutional Autoencoders Yuying Liu Colin Ponce Steven L. Brunton J. Nathan Kutz SyDa 8 30 0 10 Apr 2020
SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics Kadierdan Kaheman J. Nathan Kutz Steven L. Brunton 14 263 0 05 Apr 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 186 763 0 13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 135 510 0 11 Mar 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 91 389 0 10 Mar 2020
Connecting GANs, MFGs, and OT Haoyang Cao Xin Guo Mathieu Laurière GAN 26 14 0 10 Feb 2020
Physics Informed Deep Learning for Transport in Porous Media. Buckley Leverett Problem Cedric G. Fraces Adrien Papaioannou H. Tchelepi AI4CE PINN 33 19 0 15 Jan 2020
Enforcing Deterministic Constraints on Generative Adversarial Networks for Emulating Physical Systems Zeng Yang Jin-Long Wu Heng Xiao AI4CE 17 17 0 15 Nov 2019
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs Liu Yang Sean Treichler Thorsten Kurth Keno Fischer D. Barajas-Solano ... Valentin Churavy A. Tartakovsky Michael Houston P. Prabhat George Karniadakis AI4CE 47 38 0 29 Oct 2019
Wasserstein GANs for MR Imaging: from Paired to Unpaired Training Ke Lei Morteza Mardani John M. Pauly S. Vasanawala GAN MedIm 46 64 0 15 Oct 2019
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs Xuhui Meng Zhen Li Dongkun Zhang George Karniadakis PINN AI4CE 22 443 0 23 Sep 2019
Physics-informed semantic inpainting: Application to geostatistical modeling Q. Zheng L. Zeng Zhendan Cao George Karniadakis GAN 27 54 0 19 Sep 2019
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data Hao Xu Haibin Chang Dongxiao Zhang AI4CE 22 69 0 13 Aug 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 52 1,491 0 10 Jul 2019
Encoding Invariances in Deep Generative Models Viraj Shah Ameya Joshi Sambuddha Ghosal B. Pokuri Soumik Sarkar Baskar Ganapathysubramanian Chinmay Hegde PINN GAN 19 30 0 04 Jun 2019
Enforcing Statistical Constraints in Generative Adversarial Networks for Modeling Chaotic Dynamical Systems Jin-Long Wu K. Kashinath A. Albert D. Chirila P. Prabhat Heng Xiao AI4CE 17 133 0 13 May 2019
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs G. Abbati Philippe Wenk Michael A. Osborne Andreas Krause Bernhard Schölkopf Stefan Bauer DiffM 9 15 0 22 Feb 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 46 854 0 18 Jan 2019
Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems Yibo Yang P. Perdikaris SyDa BDL AI4CE 29 55 0 15 Jan 2019
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yibo Yang P. Perdikaris AI4CE PINN 41 355 0 09 Nov 2018
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems Dongkun Zhang Lu Lu Ling Guo George Karniadakis UQCV 27 399 0 21 Sep 2018
C-RNN-GAN: Continuous recurrent neural networks with adversarial training Olof Mogren GAN 77 515 0 29 Nov 2016