Proposes sCWL, fCWL, maximal clique complex, and CliqueWalk sampling to create a scalable higher-order graph learning framework that preserves expressivity.
CIN++: Enhancing topological message passing.arXiv preprint arXiv:2306.03561, 2023
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Scaling Higher-Order Graph Learning with Maximal Clique Complexes
Proposes sCWL, fCWL, maximal clique complex, and CliqueWalk sampling to create a scalable higher-order graph learning framework that preserves expressivity.