How powerful are graph neural networks?
Beyond Weisfeiler-Lehman: approximate isomorphisms and metric embeddings
In this post, I argue that the graph isomorphism setting is too limiting for analysing the expressive power of graph neural networks and suggest a broader setting based on metric embeddings.
Published in
6 min readJul 13, 2020
