13 citations · 13 across the 2 of their papers we have counts for
2 papers
math.NA2024
Variational formulation based on duality to solve partial differential equations: Use of B-splines and machine learning approximants
N. Sukumar, Amit Acharya
Many partial differential equations (PDEs) such as Navier--Stokes equations in fluid mechanics, inelastic deformation in solids, and transient parabolic and hyperbolic equations do…
cs.LG2022★ 13 cited
FO-PINNs: A First-Order formulation for Physics Informed Neural Networks
Rini J. Gladstone, Mohammad A. Nabian, N. Sukumar +2
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 incorpor…