Correcting model misspecification in physics-informed neural networks
(PINNs)

Correcting model misspecification in physics-informed neural networks (PINNs)

16 October 2023

George Karniadakis

Papers citing "Correcting model misspecification in physics-informed neural networks (PINNs)"

9 / 9 papers shown

Title
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method Conor Rowan K. Maute Alireza Doostan AI4CE 36 0 0 08 May 2025
Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble Zongren Zou Zhicheng Wang George Karniadakis PINN AI4CE 65 2 0 08 Mar 2025
Physics-informed deep learning for infectious disease forecasting Y. Qian Éric Marty Avranil Basu Avranil Basu Eamon B. O'Dea Xianqiao Wang Spencer Fox Pejman Rohani John M. Drake He Li PINN AI4CE 78 2 0 16 Jan 2025
Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information S. Malani Tom S. Bertalan Tianqi Cui J. Avalos Michael Betenbaugh Ioannis G. Kevrekidis PINN AI4CE 32 4 0 27 Apr 2023
Leveraging Multi-time Hamilton-Jacobi PDEs for Certain Scientific Machine Learning Problems Paula Chen Tingwei Meng Zongren Zou Jérome Darbon George Karniadakis AI4CE 25 5 0 22 Mar 2023
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 170 756 0 13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 506 0 11 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016
MCMC using Hamiltonian dynamics Radford M. Neal 132 3,263 0 09 Jun 2012