Active training of physics-informed neural networks to aggregate and interpolate parametric solutions to the Navier-Stokes equations
Work
Year: 2021
Type: article
Abstract: The goal of this work is to train a neural network which approximates solutions to the Navier-Stokes equations across a region of parameter space, in which the parameters define physical properties su... more
Source: Journal of Computational Physics
Institutions St Thomas' Hospital, King's College London
Cites: 37
Cited by: 46
Related to: 10
FWCI: 4.51
Citation percentile (by year/subfield): 78.68
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
APC paid (est): $3,750
Funder Wellcome Trust