HGPM learns compositional patterns in hypergraphs by subset tokenization and inclusion-aware masked Transformer reconstruction, matching or exceeding SOTA on ten benchmarks and correctly identifying inhibitory drug additions in adverse-event prediction where prior methods fail.
HyperGCN: A new method for training graph convolutional networks on hypergraphs
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Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions
HGPM learns compositional patterns in hypergraphs by subset tokenization and inclusion-aware masked Transformer reconstruction, matching or exceeding SOTA on ten benchmarks and correctly identifying inhibitory drug additions in adverse-event prediction where prior methods fail.