Refinement of polygonal grids using Convolutional Neural Networks with
applications to polygonal Discontinuous Galerkin and Virtual Element methods

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Refinement of polygonal grids using Convolutional Neural Networks with applications to polygonal Discontinuous Galerkin and Virtual Element methods

10 February 2021

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Papers citing "Refinement of polygonal grids using Convolutional Neural Networks with applications to polygonal Discontinuous Galerkin and Virtual Element methods"

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Title
A Deep Learning algorithm to accelerate Algebraic Multigrid methods in Finite Element solvers of 3D elliptic PDEs Matteo Caldana P. Antonietti Luca Dede' 55 11 0 21 Apr 2023
Agglomeration of Polygonal Grids using Graph Neural Networks with applications to Multigrid solvers P. Antonietti N. Farenga E. Manuzzi G. Martinelli L. Saverio AI4CE 60 22 0 31 Oct 2022
Quasi-optimal $hp$ -finite element refinements towards singularities via deep neural network prediction Tomasz Sluzalec R. Grzeszczuk Sergio Rojas W. Dzwinel Maciej Paszyñski 53 7 0 13 Sep 2022
Learning robust marking policies for adaptive mesh refinement A. Gillette B. Keith S. Petrides 63 11 0 13 Jul 2022
Machine Learning based refinement strategies for polyhedral grids with applications to Virtual Element and polyhedral Discontinuous Galerkin methods Paola F. Anotnietti F. Dassi E. Manuzzi 57 16 0 25 Feb 2022