A multifidelity approach to continual learning for physical systems

8 April 2023

Papers citing "A multifidelity approach to continual learning for physical systems"

5 / 5 papers shown

Title
Transfer Learning on Multi-Dimensional Data: A Novel Approach to Neural Network-Based Surrogate Modeling Adrienne M. Propp Daniel M. Tartakovsky AI4CE 23 2 0 16 Oct 2024
Machine learning of hidden variables in multiscale fluid simulation A. Joglekar A. Thomas AI4CE 53 8 0 19 Jun 2023
Applying Machine Learning to Study Fluid Mechanics Steven L. Brunton PINN AI4CE 37 94 0 05 Oct 2021
DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks Christian Moya Guang Lin AI4CE PINN 48 37 0 09 Sep 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 69 218 0 26 Apr 2021