UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks

3 May 2021 Jing Huang Jie Yang

Hypergraph, an expressive structure with flexibility to model the higher-order correlations among entities, has recently attracted increasing attention from various research domains. Despite the success of Graph Neural Networks (GNNs) for graph representation learning, how to adapt the powerful GNN-variants directly into hypergraphs remains a challenging problem... (read more)

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