Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next
Work
Year: 2022
Type: article
Abstract: Physics-Informed Neural Networks (PINN) are neural networks (NNs) that encode model equations, like Partial Differential Equations (PDE), as a component of the neural network itself. PINNs are nowaday... more
Source: Journal of Scientific Computing
Authors Salvatore Cuomo, Vincenzo Schiano Di Cola, Fabio Giampaolo, Gianluigi Rozza, Maziar Raissi +1 more
Institutions University of Naples Federico II, Scuola Internazionale Superiore di Studi Avanzati, University of Colorado Boulder
Cites: 174
Cited by: 994
Related to: 10
FWCI: 132.1
Citation percentile (by year/subfield): 99.98
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
APC paid (est): $2,990