What is GNNs?

Graph Neural Networks (GNNs) are a class of neural networks designed to operate on graph-structured data. They learn representations of nodes, edges, or entire graphs by iteratively aggregating and transforming information from their neighbors. GNNs are commonly used in various applications such as node classification, link prediction, graph classification, and graph generation. Examples include social network analysis, drug discovery, recommendation systems, and traffic prediction.