Approximation of symmetric total variation on point clouds
Analysis of PDEs
2026-03-31 v1 Probability
Abstract
The paper investigates the approximation of the symmetric Total Variation functional on graphs. Such an approximation is given in terms of a discrete and symmetric finite difference model defined on point clouds obtained by randomly sampling a reference probability measure. We identify suitable scalings of the point distribution that guarantee an almost surely -convergence to an anisotropic weighted symmetric Total Variation.
Cite
@article{arxiv.2603.28172,
title = {Approximation of symmetric total variation on point clouds},
author = {Stefano Almi and Anna Kubin and Emanuele Tasso},
journal= {arXiv preprint arXiv:2603.28172},
year = {2026}
}