14 citations · 26 across the 6 of their papers we have counts for
4 papers · 1 filter
Unfitted finite element interpolated neural networks
Wei Li, Alberto F. Martín, Santiago Badia
We present a novel approach that integrates unfitted finite element methods and neural networks to approximate partial differential equations on complex geometries. Easy-to-generat…
Compatible finite element interpolated neural networks
Santiago Badia, Wei Li, Alberto F. Martín
We extend the finite element interpolated neural network (FEINN) framework from partial differential equations (PDEs) with weak solutions in to PDEs with weak solutions in $H…
STLCutters.jl: A scalable geometrical framework library for unfitted finite element discretisations
Pere A. Martorell, Santiago Badia
Approximating partial differential equations for extensive industrial and scientific applications requires leveraging the power of modern high-performance computing. In large-scale…
Adaptive Finite Element Interpolated Neural Networks
Santiago Badia, Wei Li, Alberto F. Martín
The use of neural networks to approximate partial differential equations (PDEs) has gained significant attention in recent years. However, the approximation of PDEs with localised…