Graph Theory

Graph Neural Networks (GNNs) are a class of deep learning models that effectively process data represented as graphs. They learn to capture relationships and dependencies between nodes and edges, making them ideal for tasks like social network analysis, molecule modeling, and recommendation systems by leveraging the graph's structure for improved accuracy.