Oral Poster
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning
Raffaele Paolino · Sohir Maskey · Pascal Welke · Gitta Kutyniok
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Abstract
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Oral
presentation:
Oral Session 5A
Fri 13 Dec 10 a.m. PST — 11 a.m. PST
Fri 13 Dec 11 a.m. PST
— 2 p.m. PST
Fri 13 Dec 10 a.m. PST — 11 a.m. PST
Abstract:
We introduce $r$-loopy Weisfeiler-Leman ($r$-$\ell$WL), a novel hierarchy of graph isomorphism tests and a corresponding GNN framework, $r$-$\ell$MPNN, that can count cycles up to length $r{+}2$. Most notably, we show that $r$-$\ell$WL can count homomorphisms of cactus graphs. This extends 1-WL, which can only count homomorphisms of trees and, in fact, is incomparable to $k$-WL for any fixed $k$. We empirically validate the expressive and counting power of $r$-$\ell$MPNN on several synthetic datasets and demonstrate the scalability and strong performance on various real-world datasets, particularly on sparse graphs.
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