Antoine Vialle
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126
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ML×1AI×1
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2026
Scaling Higher-Order Graph Learning with Maximal Clique Complexes
This paper proposes a scalable topological learning framework for higher-order graph representation by introducing simplified and factored cellular Weisfeiler Leman tests and a novel random walk method for sampling maximal cliques.
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