Meta-learning PINN loss functions

Meta-learning PINN loss functions

12 July 2021

Apostolos F. Psaros

Kenji Kawaguchi

George Karniadakis

Papers citing "Meta-learning PINN loss functions"

14 / 14 papers shown

Title
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 20 10 0 08 Oct 2023
Learning Specialized Activation Functions for Physics-informed Neural Networks Honghui Wang Lu Lu Shiji Song Gao Huang PINN AI4CE 16 12 0 08 Aug 2023
Efficient Training of Physics-Informed Neural Networks with Direct Grid Refinement Algorithm Shikhar Nilabh F. Grandia 39 1 0 14 Jun 2023
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs Yanlai Chen Shawn Koohy PINN AI4CE 37 24 0 27 Mar 2023
Improving physics-informed neural networks with meta-learned optimization Alexander Bihlo PINN 36 18 0 13 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 29 28 0 03 Mar 2023
PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss Fabian Heldmann Sarah Treibert Matthias Ehrhardt K. Klamroth 38 20 0 03 Feb 2023
Online Loss Function Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang 38 5 0 30 Jan 2023
Super-Resolution Analysis via Machine Learning: A Survey for Fluid Flows Kai Fukami K. Fukagata Kunihiko Taira AI4CE 19 104 0 26 Jan 2023
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang FedML 29 11 0 19 Sep 2022
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu Min Zhu Qinyan Tan Yadhu Kartha Lu Lu 32 353 0 21 Jul 2022
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 101 274 0 20 Apr 2021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 183 760 0 13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 128 509 0 11 Mar 2020