19 citations · 21 across the 2 of their papers we have counts for
5 papers · 1 filter
A Deep Fourier Residual Method for solving PDEs using Neural Networks
Jamie M. Taylor, David Pardo, Ignacio Muga
When using Neural Networks as trial functions to numerically solve PDEs, a key choice to be made is the loss function to be minimised, which should ideally correspond to a norm of…
Isogeometric Residual Minimization Method (iGRM) with Direction Splitting for Non-Stationary Advection-Diffusion Problems
Marcin Los, Judit Munoz-Matute, Ignacio Muga +1
In this paper, we propose a novel computational implicit method, which we call Isogeometric Residual Minimization (iGRM) with direction splitting. The method mixes the benefits res…
Isogeometric Residual Minimization (iGRM) for Non-Stationary Stokes and Navier-Stokes Problems
Marcin Los, Ignacio Muga, Judit Munoz-Matute +1
We show that it is possible to obtain a linear computational cost FEM-based solver for non-stationary Stokes and Navier-Stokes equations. Our method employs a technique developed b…
An adaptive stabilized conforming finite element method via residual minimization on dual discontinuous Galerkin norms
Victor M. Calo, Alexandre Ern, Ignacio Muga +1
We design and analyze a new adaptive stabilized finite element method. We construct a discrete approximation of the solution in a continuous trial space by minimizing the residual…
Isogeometric Residual Minimization Method (iGRM) with Direction Splitting Preconditoner for Stationary Advection-Diffusion Problems
Victor M Calo, Marcin Łoś, Quanling Deng +2
In this paper, we introduce the isoGeometric Residual Minimization (iGRM) method. The method solves stationary advection-dominated diffusion problems. We stabilize the method via r…