research
∙
06/08/2023
Multilevel domain decomposition-based architectures for physics-informed neural networks
Physics-informed neural networks (PINNs) are a popular and powerful appr...
share
research
∙
05/31/2023
Are Neural Operators Really Neural Operators? Frame Theory Meets Operator Learning
Recently, there has been significant interest in operator learning, i.e....
research
∙
11/10/2022
Finite basis physics-informed neural networks as a Schwarz domain decomposition method
Physics-informed neural networks (PINNs) [4, 10] are an approach for sol...
research
∙
08/13/2020
Iterative Surrogate Model Optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks
We present a novel active learning algorithm, termed as iterative surrog...
research
∙
06/29/2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs II: A class of inverse problems
Physics informed neural networks (PINNs) have recently been very success...
research
∙
06/29/2020
