A survey on hypergraph representation learning
Hypergraphs have attracted increasing attention in recent years thanks to their flexibility in
naturally modeling a broad range of systems where high-order relationships exist among …
naturally modeling a broad range of systems where high-order relationships exist among …
Dual-view hypergraph neural networks for attributed graph learning
Graph embedding analyzes network data by learning the vector representation of each
vertex in the network, and has attracted widespread attention in recent years. In many real …
vertex in the network, and has attracted widespread attention in recent years. In many real …
Visualization and Extraction of Important Structural Changes via Dynamic Hypergraph Embedding
S Ito, T Fushimi - 2022 IEEE/WIC/ACM International Joint …, 2022 - ieeexplore.ieee.org
Some real-world networks have structures that change dynamically over time. These
changes include the addition or deletion of nodes and edges, and the rewiring of edges …
changes include the addition or deletion of nodes and edges, and the rewiring of edges …