Graph Neural Networks (GNNs)

A graph neural network learns from a graph. Through message passing, each node updates its representation using information from connected neighbors.

Japanese terms

1. Graph neural network — グラフニューラルネットワーク: A neural network designed to learn from nodes, edges, and relationships in graph-structured data.
2. Graph — グラフ: A structure consisting of entities represented as vertices and relationships represented as edges.
3. Message passing — メッセージパッシング: A graph-learning procedure in which nodes update their representations using information from neighboring nodes.

Related topics

Graph neural networks extend neural networks to relational structures.