Distributed physics informed neural network for data-efficient solution to partial differential equations

21 July 2019

Papers citing "Distributed physics informed neural network for data-efficient solution to partial differential equations"

6 / 6 papers shown

Title
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 49 0 14 Nov 2022
A composable machine-learning approach for steady-state simulations on high-resolution grids Rishikesh Ranade C. Hill Lalit Ghule Jay Pathak AI4CE 33 7 0 11 Oct 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 49 25 0 14 May 2022
A composable autoencoder-based iterative algorithm for accelerating numerical simulations Rishikesh Ranade C. Hill Haiyang He Amir Maleki Norman Chang Jay Pathak AI4CE 41 5 0 07 Oct 2021
Characterizing possible failure modes in physics-informed neural networks Aditi S. Krishnapriyan A. Gholami Shandian Zhe Robert M. Kirby Michael W. Mahoney PINN AI4CE 51 610 0 02 Sep 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 48 210 0 16 Jul 2021