Learning from Integral Losses in Physics Informed Neural Networks

27 May 2023

Papers citing "Learning from Integral Losses in Physics Informed Neural Networks"

7 / 7 papers shown

Title
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model M. Hassanaly Peter J. Weddle Ryan N. King Subhayan De Alireza Doostan Corey R. Randall Eric J. Dufek Andrew M. Colclasure Kandler Smith 19 6 0 28 Dec 2023
An Experimental Comparison Between Temporal Difference and Residual Gradient with Neural Network Approximation Shuyu Yin Tao Luo Peilin Liu Z. Xu 11 2 0 25 May 2022
On the Importance of Firth Bias Reduction in Few-Shot Classification Saba Ghaffari Ehsan Saleh David A. Forsyth Yu-xiong Wang 20 13 0 06 Oct 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 98 272 0 20 Apr 2021
Understanding self-supervised Learning Dynamics without Contrastive Pairs Yuandong Tian Xinlei Chen Surya Ganguli SSL 138 278 0 12 Feb 2021
Meta Pseudo Labels Hieu H. Pham Zihang Dai Qizhe Xie Minh-Thang Luong Quoc V. Le VLM 245 655 0 23 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 506 0 11 Mar 2020