4 citations · 12 across the 6 of their papers we have counts for
3 papers · 1 filter
Robust Variational Physics-Informed Neural Networks
Sergio Rojas, Paweł Maczuga, Judit Muñoz-Matute +2
We introduce a Robust version of the Variational Physics-Informed Neural Networks method (RVPINNs). As in VPINNs, we define the quadratic loss functional in terms of a Petrov-Galer…
Deep Fourier Residual method for solving time-harmonic Maxwell's equations
Jamie M. Taylor, Manuela Bastidas, David Pardo +1
Solving PDEs with machine learning techniques has become a popular alternative to conventional methods. In this context, Neural networks (NNs) are among the most commonly used mach…
Machine Learning Discovery of Optimal Quadrature Rules for Isogeometric Analysis
Tomas Teijeiro, Jamie M. Taylor, Ali Hashemian +1
We propose the use of machine learning techniques to find optimal quadrature rules for the construction of stiffness and mass matrices in isogeometric analysis (IGA). We initially…