Graph neural networks (GNNs) are specialised deep learning architectures designed to operate on data represented as graphs, where entities are modelled as nodes and relationships as edges. In ...

Graph-based learning techniques traditionally focus on pairwise relationships, modelling them as edges between two nodes. Hypergraphs generalise this concept by allowing edges—known as hyperedges—to ...