GNN (Graph Neural Networks)

Graph Neural Networks (GNNs) are a type of AI model designed to analyze data structured as graphs—networks of interconnected nodes (entities) and edges (relationships). Imagine social networks where people (nodes) connect through friendships (edges); GNNs learn to understand patterns and properties within such complex, interconnected data. They do this by iteratively sharing and updating information between nodes based on their neighbors, enabling the network to capture both local and global structures. GNNs are powerful for tasks like recommendation systems, biological data analysis, and understanding social interactions, where understanding relationships is key.