25 citations · 47 across the 2 of their papers we have counts for
2 papers
math.NA2022★ 22 cited
Machine Learning based refinement strategies for polyhedral grids with applications to Virtual Element and polyhedral Discontinuous Galerkin methods
P. F. Antonietti, F. Dassi, E. Manuzzi
We propose two new strategies based on Machine Learning techniques to handle polyhedral grid refinement, to be possibly employed within an adaptive framework. The first one employs…
math.NA2021★ 25 cited
Refinement of polygonal grids using Convolutional Neural Networks with applications to polygonal Discontinuous Galerkin and Virtual Element methods
P. F. Antonietti, E. Manuzzi
We propose new strategies to handle polygonal grids refinement based on Convolutional Neural Networks (CNNs). We show that CNNs can be successfully employed to identify correctly t…