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...

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Chi tiết về thư mục
Những tác giả chính:	Frasca, F, Bevilacqua, B, Bronstein, M, Maron, H
Định dạng:	Conference item
Ngôn ngữ:	English
Được phát hành:	Curran Associates 2022

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