2 papers
cs.LG2025
Cayley Graph Propagation
JJ Wilson, Maya Bechler-Speicher, Petar VeliÄkoviÄ
In spite of the plethora of success stories with graph neural networks (GNNs) on modelling graph-structured data, they are notoriously vulnerable to over-squashing, whereby tasks n…
cs.LG2024
Deep Equilibrium Algorithmic Reasoning
Dobrik Georgiev, JJ Wilson, Davide Buffelli +1
Neural Algorithmic Reasoning (NAR) research has demonstrated that graph neural networks (GNNs) could learn to execute classical algorithms. However, most previous approaches have a…