A novel meta-learning initialization method for physics-informed neural networks

23 July 2021

Papers citing "A novel meta-learning initialization method for physics-informed neural networks"

8 / 8 papers shown

Title
Challenges and opportunities for machine learning in multiscale computational modeling Phong C. H. Nguyen Joseph B. Choi H. Udaykumar Stephen Seung-Yeob Baek AI4CE 16 8 0 22 Mar 2023
Improving physics-informed neural networks with meta-learned optimization Alexander Bihlo PINN 26 18 0 13 Mar 2023
Scaling transformation of the multimode nonlinear Schrödinger equation for physics-informed neural networks I. Chuprov D. Efremenko Jiexing Gao P. Anisimov V. Zemlyakov 9 0 0 29 Sep 2022
Multi-Objective Loss Balancing for Physics-Informed Deep Learning Rafael Bischof M. Kraus PINN AI4CE 14 88 0 19 Oct 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 98 271 0 20 Apr 2021
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 506 0 11 Mar 2020
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 165 666 0 07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,659 0 09 Mar 2017