Keywords
Partial differential equationNonlinear systemArtificial neural networkContext (archaeology)Inverse problemPartial derivativeComputer scienceAutomatic differentiationApplied mathematicsPhysical lawMathematicsArtificial intelligenceAlgorithmMathematical analysisPhysics
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Publication Info
- Year
- 2018
- Type
- article
- Volume
- 378
- Pages
- 686-707
- Citations
- 12848
- Access
- Closed
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Cite This
Maziar Raissi,
Paris Perdikaris,
George Em Karniadakis
(2018).
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.
Journal of Computational Physics
, 378
, 686-707.
https://doi.org/10.1016/j.jcp.2018.10.045
Identifiers
- DOI
- 10.1016/j.jcp.2018.10.045