MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics

28 January 2023

Papers citing "MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics"

6 / 6 papers shown

Title
Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model for Complex Material Responses S. Jafarzadeh Stewart Silling Ning Liu Zhongqiang Zhang Yue Yu AI4CE 21 15 0 11 Jan 2024
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs Yanlai Chen Shawn Koohy PINN AI4CE 23 24 0 27 Mar 2023
Multiwavelet-based Operator Learning for Differential Equations Gaurav Gupta Xiongye Xiao P. Bogdan 124 200 0 28 Sep 2021
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML Aniruddh Raghu M. Raghu Samy Bengio Oriol Vinyals 172 639 0 19 Sep 2019
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 191 498 0 11 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,677 0 09 Mar 2017