Topologically Attributed Graphs for Shape Discrimination
Algebraic Topology
2023-07-03 v1 Computational Geometry
Abstract
In this paper we introduce a novel family of attributed graphs for the purpose of shape discrimination. Our graphs typically arise from variations on the Mapper graph construction, which is an approximation of the Reeb graph for point cloud data. Our attributions enrich these constructions with (persistent) homology in ways that are provably stable, thereby recording extra topological information that is typically lost in these graph constructions. We provide experiments which illustrate the use of these invariants for shape representation and classification. In particular, we obtain competitive shape classification results when using our topologically attributed graphs as inputs to a simple graph neural network classifier.
Cite
@article{arxiv.2306.17805,
title = {Topologically Attributed Graphs for Shape Discrimination},
author = {Justin Curry and Washington Mio and Tom Needham and Osman Berat Okutan and Florian Russold},
journal= {arXiv preprint arXiv:2306.17805},
year = {2023}
}