researcher

David Pardo

University of the Basque Country (UPV/EHU)

9 papers hereh-index 314.4k citations176 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position

middle author7
last author2

Across the 9 of 9 papers where every author was matched, so the position is known.

fields

affiliations

University of the Basque Country (UPV/EHU)
Basque Center for Applied Mathematics (BCAM)
Ikerbasque

Homepage

same name

David Pardo — 11 papers, h 6
David Pardo — 2 papers, h 3
David Pardo — 2 papers, h 1
David Pardo — 1 paper, h 0
David Pardo — 1 paper, h 2
David Pardo — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity

20182022

most citedA Deep Double Ritz Method (D

^{2}

RM) for solving Partial Differential Equations using Neural Networks

19 citations · 20 across the 3 of their papers we have counts for

collaborators

Showing 2022 · math.NAShow all

2 papers · 2 filters

math.NA2022★ 19 cited

A Deep Double Ritz Method (D $^{2}$ RM) for solving Partial Differential Equations using Neural Networks

Carlos Uriarte, David Pardo, Ignacio Muga +1

Residual minimization is a widely used technique for solving Partial Differential Equations in variational form. It minimizes the dual norm of the residual, which naturally yields…

math.NA2022★ 1 cited

$r -$ Adaptive Deep Learning Method for Solving Partial Differential Equations

Ángel J. Omella, David Pardo

We introduce an $r -$ adaptive algorithm to solve Partial Differential Equations using a Deep Neural Network. The proposed method restricts to tensor product meshes and optimizes the…

A Deep Double Ritz Method (D2RM) for solving Partial Differential Equations using Neural Networks

r−Adaptive Deep Learning Method for Solving Partial Differential Equations

A Deep Double Ritz Method (D $^{2}$ RM) for solving Partial Differential Equations using Neural Networks

$r -$ Adaptive Deep Learning Method for Solving Partial Differential Equations