Graph Neural Networks
Graph Neural Networks are a type of neural network specifically designed to operate on graph data structures, such as social networks, citation networks, and molecular structures. They leverage information from the nodes and edges of the graph to perform tasks such as node classification, link prediction, and graph classification. Graph Neural Networks have gained popularity in recent years for their ability to model complex relationships and dependencies in graph data, making them well-suited for a wide range of applications in various fields including social media analysis, recommendation systems, and drug discovery.