1.  The WL algorithm aggregates and updates discrete labels (using a hash function) while GNN models aggregate and update node embeddings using neural networks.
2. GNNs have been motivated and derived as a continuous and differentiable analog of the WL algorithm.


University of Illinois at Urbana-Champaign

1. The key distinction between GNN and WL.
2. The relationship between GNNs and the WL algorithm.

GNNs and the WL Algorithm

Hamilton, W.L. Graph Representation Learning. *Synthesis Lectures on Artificial Intelligence and Machine Learning*. 2020, 14(3), 1–159. https://doi.org/10.2200/S01045ED1V01Y202009AIM046

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