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

We introduce physics-informed neural networks – neural networks that are trained to solve supervised learning tasks while respecting any given laws of physics described by general nonlinear partial differential equations. In this work, we present our developments in the context of solving two main c...

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