A Novel Higher-order Weisfeiler-Lehman Graph Convolution

Understand

Current GNN architectures use a vertex neighborhood aggregation scheme, which limits their discriminative power to that of the 1-dimensional Weisfeiler-Lehman (WL) graph isomorphism test.

• Here, we propose a novel graph convolution operator that is based on the 2-dimensional WL test.
• We formally show that the resulting 2-WL-GNN architecture is more discriminative than existing GNN approaches.
• This theoretical result is complemented by experimental studies using synthetic and real data.