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cs.LG2024
Homomorphism Counts as Structural Encodings for Graph Learning
Linus Bao, Emily Jin, Michael Bronstein +2
Graph Transformers are popular neural networks that extend the well-known Transformer architecture to the graph domain. These architectures operate by applying self-attention on gr…
cs.LG2024★ 1 cited
Homomorphism Counts for Graph Neural Networks: All About That Basis
Emily Jin, Michael Bronstein, İsmail İlkan Ceylan +1
A large body of work has investigated the properties of graph neural networks and identified several limitations, particularly pertaining to their expressive power. Their inability…