Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networks

30 August 2021

Papers citing "Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networks"

10 / 10 papers shown

Title
A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty Mingtao Xia Qijing Shen 24 1 0 10 Jun 2024
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification Qianli Shen Wai Hoh Tang Zhun Deng Apostolos F. Psaros Kenji Kawaguchi 60 1 0 10 Oct 2023
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires J. Dabrowski D. Pagendam J. Hilton Conrad Sanderson Dan MacKinlay C. Huston Andrew Bolt Petra Kuhnert PINN 27 17 0 02 Dec 2022
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 24 17 0 27 Oct 2022
Solving Coupled Differential Equation Groups Using PINO-CDE Wenhao Ding Qing He Hanghang Tong Qingjing Wang Ping Wang OOD AI4CE 27 4 0 01 Oct 2022
Neural Networks Based on Power Method and Inverse Power Method for Solving Linear Eigenvalue Problems Qihong Yang Yangtao Deng Yu Yang Qiaolin He Shiquan Zhang 16 13 0 22 Sep 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic Barbara Z Cunha C. Droz A. Zine Stéphane Foulard M. Ichchou AI4CE 29 84 0 13 Apr 2022
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems Katiana Kontolati Dimitrios Loukrezis D. D. Giovanis Lohit Vandanapu Michael D. Shields 25 40 0 09 Feb 2022
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 180 758 0 13 Mar 2020
Conditional Image Synthesis With Auxiliary Classifier GANs Augustus Odena C. Olah Jonathon Shlens GAN 238 3,190 0 30 Oct 2016