Solving inverse-PDE problems with physics-aware neural networks

10 Jan 2020Samira PakravanPouria A. MistaniMiguel Angel Aragon-CalvoFrederic Gibou

We propose a novel composite framework that enables finding unknown fields in the context of inverse problems for partial differential equations (PDEs). We blend the high expressibility of deep neural networks as universal function estimators with the accuracy and reliability of existing numerical algorithms for partial differential equations... (read more)

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