Search Results for author: Mohammad A. Nabian

Found 1 papers, 0 papers with code

FO-PINNs: A First-Order formulation for Physics Informed Neural Networks

no code implementations25 Oct 2022 Rini J. Gladstone, Mohammad A. Nabian, N. Sukumar, Ankit Srivastava, Hadi Meidani

Physics-Informed Neural Networks (PINNs) are a class of deep learning neural networks that learn the response of a physical system without any simulation data, and only by incorporating the governing partial differential equations (PDEs) in their loss function.

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