Adversarial Uncertainty Quantification in Physics-Informed Neural Networks

9 November 2018

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

50 / 135 papers shown

Title
Generative Modeling of Random Fields from Limited Data via Constrained Latent Flow Matching James E. Warner Tristan A. Shah Patrick E. Leser Geoffrey F. Bomarito Joshua D. Pribe Michael C. Stanley AI4CE 15 0 0 19 May 2025
SPIEDiff: robust learning of long-time macroscopic dynamics from short-time particle simulations with quantified epistemic uncertainty Zequn He Celia Reina DiffM AI4CE 7 0 0 16 May 2025
Multi-fidelity Parameter Estimation Using Conditional Diffusion Models Caroline Tatsuoka Minglei Yang Dongbin Xiu Guannan Zhang DiffM 49 1 0 02 Apr 2025
Scalable physics-informed deep generative model for solving forward and inverse stochastic differential equations Shaoqian Zhou Wen You Ling Guo Xuhui Meng DiffM MedIm 56 0 0 23 Mar 2025
BPINN-EM-Post: Stochastic Electromigration Damage Analysis in the Post-Void Phase based on Bayesian Physics-Informed Neural Network Subed Lamichhane Haotian Lu Sheldon X.-D. Tan 34 0 0 18 Mar 2025
Model Based and Physics Informed Deep Learning Neural Network Structures A. Mohammad-Djafari Ning Chu Li Wang Caifang Cai Liang Yu PINN 41 0 0 13 Aug 2024
Scalable Artificial Intelligence for Science: Perspectives, Methods and Exemplars Wesley Brewer Aditya Kashi Sajal Dash A. Tsaris Junqi Yin Mallikarjun Shankar Feiyi Wang 46 0 0 24 Jun 2024
VS-PINN: A fast and efficient training of physics-informed neural networks using variable-scaling methods for solving PDEs with stiff behavior Seungchan Ko Sang Hyeon Park 37 2 0 10 Jun 2024
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos P. Koutsourelakis AI4CE 41 3 0 29 May 2024
Savvy: Trustworthy Autonomous Vehicles Architecture Ali Shoker Rehana Yasmin Paulo Esteves-Verissimo 36 0 0 08 Feb 2024
Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks Youngkyoung Bae Seungwoong Ha Hawoong Jeong 73 2 0 02 Feb 2024
Approximation of Solution Operators for High-dimensional PDEs Nathan Gaby Xiaojing Ye 30 0 0 18 Jan 2024
Robust Physics Informed Neural Networks Marcin Lo's Maciej Paszyñski PINN 14 0 0 04 Jan 2024
Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks Zheyuan Hu Zekun Shi George Karniadakis Kenji Kawaguchi AI4CE PINN 52 24 0 22 Dec 2023
Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities Wenchong He Zhe Jiang 32 1 0 04 Nov 2023
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification Qianli Shen Wai Hoh Tang Zhun Deng Apostolos F. Psaros Kenji Kawaguchi 96 1 0 10 Oct 2023
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 28 10 0 08 Oct 2023
Spectral operator learning for parametric PDEs without data reliance Junho Choi Taehyun Yun Namjung Kim Youngjoon Hong 27 8 0 03 Oct 2023
Tackling the Curse of Dimensionality with Physics-Informed Neural Networks Zheyuan Hu K. Shukla George Karniadakis Kenji Kawaguchi PINN AI4CE 65 88 0 23 Jul 2023
PI-VEGAN: Physics Informed Variational Embedding Generative Adversarial Networks for Stochastic Differential Equations R. Gao Yufeng Wang Min Yang Chuanjun Chen GAN 34 2 0 21 Jul 2023
Worth of knowledge in deep learning Hao Xu Yuntian Chen Dong-juan Zhang 18 0 0 03 Jul 2023
Generative Adversarial Reduced Order Modelling Dario Coscia N. Demo G. Rozza GAN AI4CE 64 5 0 25 May 2023
Reversible and irreversible bracket-based dynamics for deep graph neural networks A. Gruber Kookjin Lee N. Trask AI4CE 33 9 0 24 May 2023
Bounded KRnet and its applications to density estimation and approximation Lisheng Zeng Xiaoliang Wan Tao Zhou 25 5 0 15 May 2023
Learning Stochastic Dynamical System via Flow Map Operator Yuán Chen D. Xiu AI4CE 27 15 0 05 May 2023
A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse Regimes Minglang Yin Zongren Zou Enrui Zhang C. Cavinato J. Humphrey George Karniadakis SyDa MedIm AI4CE 53 11 0 04 May 2023
A Bi-fidelity DeepONet Approach for Modeling Uncertain and Degrading Hysteretic Systems Subhayan De P. Brewick 31 0 0 25 Apr 2023
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems Xiaofei Guan Xintong Wang Hao Wu Zihao Yang Peng Yu PINN 27 11 0 25 Apr 2023
Generating artificial digital image correlation data using physics-guided adversarial networks D. Melching Erik Schultheis Eric Breitbarth GAN AI4CE 16 2 0 28 Mar 2023
Delay-SDE-net: A deep learning approach for time series modelling with memory and uncertainty estimates M. Eggen A. Midtfjord 29 2 0 14 Mar 2023
Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook Xuan Di Rongye Shi Zhaobin Mo Yongjie Fu PINN AI4TS AI4CE 32 28 0 03 Mar 2023
A Survey on Uncertainty Quantification Methods for Deep Learning Wenchong He Zhe Jiang Tingsong Xiao Zelin Xu Yukun Li BDL UQCV AI4CE 19 19 0 26 Feb 2023
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs Zebang Shen Zhenfu Wang 23 5 0 11 Feb 2023
Neural Control of Parametric Solutions for High-dimensional Evolution PDEs Nathan Gaby X. Ye Haomin Zhou 19 6 0 31 Jan 2023
Random Grid Neural Processes for Parametric Partial Differential Equations Arnaud Vadeboncoeur Ieva Kazlauskaite Y. Papandreou F. Cirak Mark Girolami Ömer Deniz Akyildiz AI4CE 28 11 0 26 Jan 2023
Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks Olga Graf P. Flores P. Protopapas K. Pichara PINN 39 6 0 14 Dec 2022
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 33 17 0 02 Dec 2022
Investigating Deep Learning Model Calibration for Classification Problems in Mechanics S. Mohammadzadeh Peerasait Prachaseree Emma Lejeune AI4CE 34 2 0 01 Dec 2022
VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations Bin Shan Ye Li Sheng-Jun Huang PINN 29 2 0 30 Nov 2022
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 44 18 0 30 Nov 2022
Utilising physics-guided deep learning to overcome data scarcity Jinshuai Bai Laith Alzubaidi Qingxia Wang E. Kuhl Bennamoun Yuantong T. Gu PINN AI4CE 45 3 0 24 Nov 2022
Physics-Informed Koopman Network Yuying Liu A. Sholokhov Hassan Mansour S. Nabi AI4CE 31 3 0 17 Nov 2022
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology Zheyuan Hu Ameya Dilip Jagtap George Karniadakis Kenji Kawaguchi 34 75 0 16 Nov 2022
SVD-PINNs: Transfer Learning of Physics-Informed Neural Networks via Singular Value Decomposition Yihang Gao Ka Chun Cheung Michael K. Ng 38 15 0 16 Nov 2022
Physics-informed neural networks for operator equations with stochastic data Paul Escapil-Inchauspé G. A. Ruz 34 2 0 15 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 21 5 0 26 Oct 2022
Bayesian deep learning framework for uncertainty quantification in high dimensions Jeahan Jung Minseok Choi BDL UQCV 21 1 0 21 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 24 13 0 22 Sep 2022
A Model-Constrained Tangent Slope Learning Approach for Dynamical Systems Hai V. Nguyen T. Bui-Thanh 39 2 0 09 Aug 2022
Fully probabilistic deep models for forward and inverse problems in parametric PDEs Arnaud Vadeboncoeur Ömer Deniz Akyildiz Ieva Kazlauskaite Mark Girolami F. Cirak AI4CE 23 17 0 09 Aug 2022