Physics-Informed Neural Networks and Extensions
<|reference_start|>Physics-Informed Neural Networks and Extensions: 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.<|reference_end|>
@article{raissi2024physics-informed,
    title={Physics-Informed Neural Networks and Extensions},
    author={Maziar Raissi, Paris Perdikaris, Nazanin Ahmadi, and George Em
  Karniadakis},
    journal={arXiv preprint arXiv:2408.16806},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.16806},
    primaryClass={cs.LG cs.AI}
}