Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

5 November 2018

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

50 / 139 papers shown

Title
Neural PDE Solvers for Irregular Domains Biswajit Khara Ethan Herron Zhanhong Jiang Aditya Balu Chih-Hsuan Yang ... Anushrut Jignasu Soumik Sarkar Chinmay Hegde A. Krishnamurthy Baskar Ganapathysubramanian AI4CE 24 7 0 07 Nov 2022
$Adaptive deep density approximation for fractional Fokker-Planck equations$ Adaptive deep density approximation for fractional Fokker-Planck equations Li Zeng Xiaoliang Wan Tao Zhou 34 5 0 26 Oct 2022
Bayesian deep learning framework for uncertainty quantification in high dimensions Jeahan Jung Minseok Choi BDL UQCV 28 1 0 21 Oct 2022
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations Alexander New B. Eng A. Timm A. Gearhart 20 4 0 14 Oct 2022
Spectral Diffusion Processes Angus Phillips Thomas Seror M. Hutchinson Valentin De Bortoli Arnaud Doucet Emile Mathieu DiffM 69 15 0 28 Sep 2022
Deep Physics Corrector: A physics enhanced deep learning architecture for solving stochastic differential equations Tushar S. Chakraborty 41 6 0 20 Sep 2022
DEQGAN: Learning the Loss Function for PINNs with Generative Adversarial Networks Blake Bullwinkel Dylan Randle P. Protopapas David Sondak 29 3 0 15 Sep 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 36 37 0 25 Aug 2022
CP-PINNs: Data-Driven Changepoints Detection in PDEs Using Online Optimized Physics-Informed Neural Networks Zhi-Ling Dong Pawel Polak PINN 31 1 0 18 Aug 2022
PIAT: Physics Informed Adversarial Training for Solving Partial Differential Equations S. Shekarpaz Mohammad Azizmalayeri M. Rohban 31 4 0 14 Jul 2022
Predicting Opinion Dynamics via Sociologically-Informed Neural Networks Maya Okawa Tomoharu Iwata AI4CE PINN 26 20 0 07 Jul 2022
Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks Zhaobin Mo Yongjie Fu Xuan Di 33 11 0 19 Jun 2022
TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantification Zhaobin Mo Yongjie Fu Daran Xu Xuan Di AI4CE 25 17 0 19 Jun 2022
A comparison of PINN approaches for drift-diffusion equations on metric graphs J. Blechschmidt Jan-Frederik Pietschman Tom-Christian Riemer Martin Stoll M. Winkler 28 2 0 15 May 2022
Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data Xu Liu Wenjuan Yao Wei Peng Weien Zhou PINN AI4CE 51 25 0 14 May 2022
Physics-informed neural networks for PDE-constrained optimization and control Jostein Barry-Straume A. Sarshar Andrey A. Popov Adrian Sandu PINN AI4CE 34 14 0 06 May 2022
Identification of Physical Processes and Unknown Parameters of 3D Groundwater Contaminant Problems via Theory-guided U-net Tianhao He Haibin Chang Dongxiao Zhang PINN AI4CE 22 0 0 30 Apr 2022
Physics-assisted Generative Adversarial Network for X-Ray Tomography Zhen Guo J. Song George Barbastathis M. Glinsky C. Vaughan K. Larson B. Alpert Z. Levine GAN MedIm 24 9 0 07 Apr 2022
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets Subhayan De Matthew J. Reynolds M. Hassanaly Ryan N. King Alireza Doostan AI4CE 41 37 0 03 Apr 2022
PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations Weiheng Zhong Hadi Meidani DRL 30 37 0 21 Mar 2022
Magnetic Field Prediction Using Generative Adversarial Networks Stefan Pollok Nataniel Olden-Jorgensen P. S. Jørgensen Rasmus Bjørk GAN AI4CE 29 15 0 14 Mar 2022
The efficacy and generalizability of conditional GANs for posterior inference in physics-based inverse problems Deep Ray Harisankar Ramaswamy Dhruv V. Patel Assad A. Oberai CML AI4CE 24 21 0 15 Feb 2022
Energy-Based Models for Functional Data using Path Measure Tilting Jen Ning Lim Sebastian J. Vollmer Lorenz Wolf Andrew Duncan 31 3 0 04 Feb 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 36 1,190 0 14 Jan 2022
Solving time dependent Fokker-Planck equations via temporal normalizing flow Xiaodong Feng Li Zeng Tao Zhou AI4CE 36 25 0 28 Dec 2021
Adversarial sampling of unknown and high-dimensional conditional distributions M. Hassanaly Andrew Glaws Karen Stengel Ryan N. King GAN 27 21 0 08 Nov 2021
Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities Indranil Pan L. Mason Omar K. Matar AI4CE 49 45 0 07 Nov 2021
Physics-Guided Generative Adversarial Networks for Sea Subsurface Temperature Prediction Yuxin Meng Eric Rigall Xueén Chen Feng Gao Junyu Dong Sheng Chen GAN AI4CE 26 39 0 04 Nov 2021
Generative Adversarial Network for Probabilistic Forecast of Random Dynamical System K. Yeo Zan Li Wesley M. Gifford SyDa GAN AI4TS AI4CE 38 4 0 04 Nov 2021
CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method P. Chiu Jian Cheng Wong C. Ooi M. Dao Yew-Soon Ong PINN 36 207 0 29 Oct 2021
One-Shot Transfer Learning of Physics-Informed Neural Networks Shaan Desai M. Mattheakis H. Joy P. Protopapas Stephen J. Roberts PINN AI4CE 29 58 0 21 Oct 2021
Kinematically consistent recurrent neural networks for learning inverse problems in wave propagation Wrik Mallik R. Jaiman J. Jelovica AI4CE 25 3 0 08 Oct 2021
Applying Machine Learning to Study Fluid Mechanics Steven L. Brunton PINN AI4CE 44 96 0 05 Oct 2021
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs Biswajit Khara Aditya Balu Ameya Joshi Soumik Sarkar Chinmay Hegde A. Krishnamurthy Baskar Ganapathysubramanian 49 19 0 04 Oct 2021
Learning Density Distribution of Reachable States for Autonomous Systems Yue Meng Dawei Sun Zeng Qiu Md Tawhid Bin Waez Chuchu Fan 82 19 0 14 Sep 2021
Physics-Informed Deep Learning: A Promising Technique for System Reliability Assessment Taotao Zhou E. Droguett A. Mosleh AI4CE 11 25 0 24 Aug 2021
Quantum Quantile Mechanics: Solving Stochastic Differential Equations for Generating Time-Series Annie E. Paine V. Elfving Oleksandr Kyriienko 32 22 0 06 Aug 2021
Learning the temporal evolution of multivariate densities via normalizing flows Yubin Lu R. Maulik Ting Gao Felix Dietrich Ioannis G. Kevrekidis Jinqiao Duan 13 22 0 29 Jul 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 48 211 0 16 Jul 2021
Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors Dhruv V. Patel Deep Ray Assad A. Oberai AI4CE 19 37 0 06 Jul 2021
Learning Functional Priors and Posteriors from Data and Physics Xuhui Meng Liu Yang Zhiping Mao J. Ferrandis George Karniadakis AI4CE 35 61 0 08 Jun 2021
Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver Yuankai Teng Xiaoping Zhang Zhu Wang L. Ju 24 14 0 23 May 2021
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs Jérome Darbon P. Dower Tingwei Meng 19 22 0 07 May 2021
PCE-PINNs: Physics-Informed Neural Networks for Uncertainty Propagation in Ocean Modeling Björn Lütjens Catherine H. Crawford Mark S. Veillette Dava Newman 12 10 0 05 May 2021
Distributed Multigrid Neural Solvers on Megavoxel Domains Aditya Balu Sergio Botelho Biswajit Khara Vinay Rao Chinmay Hegde Soumik Sarkar Santi S. Adavani A. Krishnamurthy Baskar Ganapathysubramanian AI4CE 24 11 0 29 Apr 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 75 225 0 26 Apr 2021
Generative Adversarial Network: Some Analytical Perspectives Haoyang Cao Xin Guo GAN 40 2 0 25 Apr 2021
Monte Carlo Simulation of SDEs using GANs Jorino van Rhijn C. Oosterlee L. Grzelak Shuaiqiang Liu GAN AI4TS 32 8 0 03 Apr 2021
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data Mohamed Aziz Bhouri P. Perdikaris 31 20 0 04 Mar 2021
ISALT: Inference-based schemes adaptive to large time-stepping for locally Lipschitz ergodic systems X. Li Fei Lu F. Ye 20 3 0 25 Feb 2021