Bermuda Triangles: GNNs Fail to Detect Simple Topological StructuresDownload PDF

08 Mar 2021, 17:52 (modified: 08 Apr 2021, 05:09)GTRL 2021 PosterReaders: Everyone
Keywords: graph neural networks, graph topology
TL;DR: Graph neural networks can't reliably detect triangle structures in a graph
Abstract: Most graph neural network architectures work by message-passing node vector embeddings over the adjacency matrix, and it is assumed that they capture graph topology by doing that. We design two synthetic tasks, focusing purely on topological problems -- triangle detection and clique distance -- on which graph neural networks perform surprisingly badly, failing to detect those "bermuda" triangles. Datasets and their generation scripts are available on
Poster: png
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