Physics-Informed Neural Networks and Extensions

2024/08/29 by Raissi, Maziar, Perdikaris, Paris, Ahmadi, Nazanin +1 · 5 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)

paper · doi:10.48550/arxiv.2408.16806

Abstract

In this paper, we review the new method Physics-Informed Neural Networks (PINNs) that has become the main pillar in scientific machine learning, we present recent practical extensions, and provide a specific example in data-driven discovery of governing differential equations.

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