Ignacio Muga

About Ignacio Muga

Ignacio Muga, With an exceptional h-index of 15 and a recent h-index of 12 (since 2020), a distinguished researcher at Pontificia Universidad Católica de Valparaíso, specializes in the field of Análisis Numérico, Modelamiento Matemático, Cálculo Científico.

His recent articles reflect a diverse array of research interests and contributions to the field:

Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach

A deep Fourier residual method for solving PDEs using neural networks

An adaptive superconvergent mixed finite element method based on local residual minimization

Automatic stabilization of finite-element simulations using neural networks and hierarchical matrices

Deep Fourier Residual method for solving time-harmonic Maxwell's equations

Nanoionics from a quantum mechanics point of view: Mathematical modeling and numerical simulation

Adaptive stabilized finite elements via residual minimization onto bubble enrichments

A deep double Ritz method (D2RM) for solving partial differential equations using neural networks

Ignacio Muga Information

University

Position

Instituto de Matemáticas

Citations(all)

873

Citations(since 2020)

464

Cited By

583

hIndex(all)

15

hIndex(since 2020)

12

i10Index(all)

22

i10Index(since 2020)

16

Email

University Profile Page

Google Scholar

Ignacio Muga Skills & Research Interests

Análisis Numérico

Modelamiento Matemático

Cálculo Científico

Top articles of Ignacio Muga

Title

Journal

Author(s)

Publication Date

Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach

arXiv preprint arXiv:2304.01722

Ignacio Brevis

Ignacio Muga

David Pardo

Oscar Rodríguez

Kristoffer G van der Zee

2023/4/4

A deep Fourier residual method for solving PDEs using neural networks

Computer Methods in Applied Mechanics and Engineering

Jamie M Taylor

David Pardo

Ignacio Muga

2023/2/15

An adaptive superconvergent mixed finite element method based on local residual minimization

SIAM Journal on Numerical Analysis

Ignacio Muga

Sergio Rojas

Patrick Vega

2023/10/31

Automatic stabilization of finite-element simulations using neural networks and hierarchical matrices

Computer Methods in Applied Mechanics and Engineering

Tomasz Służalec

Mateusz Dobija

Anna Paszyńska

Ignacio Muga

Marcin Łoś

...

2023/6/1

Deep Fourier Residual method for solving time-harmonic Maxwell's equations

arXiv preprint arXiv:2305.09578

Jamie M Taylor

Manuela Bastidas

David Pardo

Ignacio Muga

2023/5/16

Nanoionics from a quantum mechanics point of view: Mathematical modeling and numerical simulation

Computer Methods in Applied Mechanics and Engineering

Paulina Sepúlveda

Ignacio Muga

Norberto Sainz

René G Rojas

Sebastián Ossandón

2023/3/15

Adaptive stabilized finite elements via residual minimization onto bubble enrichments

Computers & Mathematics with Applications

Jose G Hasbani

Paulina Sepúlveda

Ignacio Muga

Victor M Calo

Sergio Rojas

2023/12/1

A deep double Ritz method (D2RM) for solving partial differential equations using neural networks

Computer Methods in Applied Mechanics and Engineering

Carlos Uriarte

David Pardo

Ignacio Muga

Judit Muñoz-Matute

2023/2/15

Solving Partial Differential Equations using Adversarial Neural Networks

Carlos Uriarte

David Pardo

Judit Muñoz Matute

Ignacio Muga

2022

Neural control of discrete weak formulations: Galerkin, least squares & minimal-residual methods with quasi-optimal weights

Computer Methods in Applied Mechanics and Engineering

Ignacio Brevis

Ignacio Muga

Kristoffer G van der Zee

2022/12/1

Semi-analytical solutions for the problem of the electric potential set in a borehole with a highly conductive casing

GEM-International Journal on Geomathematics

Aralar Erdozain

Ignacio Muga

Victor Péron

Gabriel Pinochet

2022/12

A Deep Double Ritz Method for solving Partial Differential Equations

arXiv e-prints

Carlos Uriarte

David Pardo

Ignacio Muga

Judit Muñoz-Matute

2022/11

An adaptive superconvergent finite element method based on local residual minimization

arXiv preprint arXiv:2210.00390

Ignacio Muga

Sergio Rojas

Patrick Vega

2022/10/1

Projection in negative norms and the regularization of rough linear functionals

Numerische Mathematik

Felipe Millar

Ignacio Muga

Sergio Rojas

Kristoffer G Van der Zee

2022/4

Isogeometric residual minimization method (iGRM) with direction splitting preconditioner for stationary advection-dominated diffusion problems

Computer Methods in Applied Mechanics and Engineering

Victor M Calo

Marcin Łoś

Quanling Deng

Ignacio Muga

Maciej Paszyński

2021/1/1

A machine-learning minimal-residual (ML-MRes) framework for goal-oriented finite element discretizations

Computers & Mathematics with Applications

Ignacio Brevis

Ignacio Muga

Kristoffer G van der Zee

2021/8/1

Isogeometric residual minimization (iGRM) for non-stationary Stokes and Navier–Stokes problems

Computers & Mathematics with Applications

M Łoś

I Muga

J Muñoz-Matute

M Paszyński

2021/8/1

DGIRM: Discontinuous Galerkin based isogeometric residual minimization for the Stokes problem

Journal of Computational Science

Marcin Łoś

Sergio Rojas

Maciej Paszyński

Ignacio Muga

Victor M Calo

2021/3/1

Three-dimensional simulations of the airborne COVID-19 pathogens using the advection-diffusion model and alternating-directions implicit solver

Bulletin of the Polish Academy of Sciences. Technical Sciences

Marcin Łoś

Maciej Woźniak

Ignacio Muga

Maciej Paszynski

2021

Discretization of linear problems in Banach spaces: Residual minimization, nonlinear Petrov-Galerkin, and monotone mixed methods

SIAM Journal on Numerical Analysis

Ignacio Muga

Kristoffer G van der Zee

2020/11/24

See List of Professors in Ignacio Muga University(Pontificia Universidad Católica de Valparaíso)

Co-Authors

academic-engine