Is 3-(F)WL Enough to Distinguish All 3D Graphs?

Fuente: arXiv
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Main Author: Xu, Wanghan
Format: Preprint
Published: 2024
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author Xu, Wanghan
author_facet Xu, Wanghan
contents The problem of graph isomorphism is an important but challenging problem in the field of graph analysis, for example: analyzing the similarity of two chemical molecules, or studying the expressive ability of graph neural networks. WL test is a method to judge whether two graphs are isomorphic, but it cannot distinguish all non-isomorphic graphs. As an improvement of WL, k-WL has stronger isomorphism discrimination ability, and as k increases, its discrimination ability is strictly increasing. However, whether the isomorphic discrimination power of k-WL is strictly increasing for more complex 3D graphs, or whether there exists k that can discriminate all 3D graphs, remains unexplored. This paper attempts to explore this problem from the perspective of graph generation.
format Preprint
id arxiv_https___arxiv_org_abs_2402_08429
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Is 3-(F)WL Enough to Distinguish All 3D Graphs?
Xu, Wanghan
Other Computer Science
Artificial Intelligence
The problem of graph isomorphism is an important but challenging problem in the field of graph analysis, for example: analyzing the similarity of two chemical molecules, or studying the expressive ability of graph neural networks. WL test is a method to judge whether two graphs are isomorphic, but it cannot distinguish all non-isomorphic graphs. As an improvement of WL, k-WL has stronger isomorphism discrimination ability, and as k increases, its discrimination ability is strictly increasing. However, whether the isomorphic discrimination power of k-WL is strictly increasing for more complex 3D graphs, or whether there exists k that can discriminate all 3D graphs, remains unexplored. This paper attempts to explore this problem from the perspective of graph generation.
title Is 3-(F)WL Enough to Distinguish All 3D Graphs?
topic Other Computer Science
Artificial Intelligence
url https://arxiv.org/abs/2402.08429