Physics-Informed Neural Networks and Extensions

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

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arXiv · 2408.16806

Physics-Informed Neural Networks and Extensions

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

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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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Maziar Raissi, Paris Perdikaris, Nazanin Ahmadi, George Em Karniadakis. 2024-08-29. Physics-Informed Neural Networks and Extensions. https://arxiv.org/abs/2408.16806

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