Physics-Informed Neural Networks and Extensions

Raissi, Maziar, Perdikaris, Paris, Ahmadi, Nazanin, Karniadakis, George Em

arXiv.org Artificial Intelligence 

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.