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Ordered Subgraph Aggregation Networks. (arXiv:2206.11168v2 [cs.LG] UPDATED)
June 29, 2022, 1:11 a.m. | Chendi Qian, Gaurav Rattan, Floris Geerts, Christopher Morris, Mathias Niepert
stat.ML updates on arXiv.org arxiv.org
Numerous subgraph-enhanced graph neural networks (GNNs) have emerged
recently, provably boosting the expressive power of standard (message-passing)
GNNs. However, there is a limited understanding of how these approaches relate
to each other and to the Weisfeiler--Leman hierarchy. Moreover, current
approaches either use all subgraphs of a given size, sample them uniformly at
random, or use hand-crafted heuristics instead of learning to select subgraphs
in a data-driven manner. Here, we offer a unified way to study such
architectures by introducing a …
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