Ambiguities in neural-network-based hyperedge prediction

A hypergraph is a generalization of a graph that depicts higher-order relations. Predicting higher-order relations, i.e. hyperedges, is a fundamental problem in hypergraph studies, and has immense applications in multiple domains. Recent development of graph neural network (GNN) advanced the prediction of pair-wise relations in graphs. However, existing methods can hardly be extended to hypergraphs due to the lack of higher-order dependency in their graph embedding. In this paper, …