Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations ​

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Authors: M. Raissi, P. Perdikaris, G. E. Karniadakis
Year: 2019
Journal: Journal of Computational Physics
DOI: 10.1016/j.jcp.2018.10.045
Publisher: https://www.sciencedirect.com/science/article/pii/S0021999118307125

Keywords: pinn, physics-informed

Abstract ​

We introduce physics-informed neural networks PINNs for solving PDEs.

Cite this paper ​

@misc{pinn2019,
  title  = {Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations},
  author = {M. Raissi, P. Perdikaris, G. E. Karniadakis},
  year   = {2019},
  journal = {Journal of Computational Physics},
  doi    = {10.1016/j.jcp.2018.10.045},
  url    = {https://doi.org/10.1016/j.jcp.2018.10.045},
}

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