Graph Neural Networks explained for beginners

Graph Neural Networks (GNNs) are special computer models designed to process data represented as networks or graphs.

A graph consists of nodes (points) and edges (connections), for example a social network with people as nodes and friendships as edges.

GNNs help computers understand the relationships and structures in such networks.

This is useful for making predictions or recognizing patterns, for example in social networks, molecules, or traffic networks.

Thus, GNNs can help extract important information from complex connections.