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.
arXiv.org Artificial Intelligence
Aug-29-2024
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