Understanding and extending subgraph GNNs by rethinking their symmetries

Understanding and extending subgraph GNNs by rethinking their symmetries

Subgraph GNNs are a recent class of expressive Graph Neural Networks (GNNs) which model graphs as collections of subgraphs. So far, the design space of possible Subgraph GNN architectures as well as their basic theoretical properties are still largely unexplored. In this paper, we study the most pro...

书目详细资料
Main Authors:	Frasca, F, Bevilacqua, B, Bronstein, M, Maron, H
格式:	Conference item
语言:	English
出版:	Curran Associates 2022

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