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Physics-Informed Neural Networks and Extensions (2408.16806v1)

Published 29 Aug 2024 in cs.LG and cs.AI

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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Authors (4)
  1. Maziar Raissi (36 papers)
  2. Paris Perdikaris (61 papers)
  3. Nazanin Ahmadi (2 papers)
  4. George Em Karniadakis (216 papers)
Citations (1)