A Graph Neural Network (GNN) is a type of neural network specifically designed to work with data represented as graphs. Graphs are mathematical structures consisting of nodes (or vertices) connected by edges, which can represent various types of relationships between entities. Common applications for GNNs include social networks, molecular chemistry, recommendation systems, and knowledge graphs. ### Key Features of Graph Neural Networks: 1. **Graph Structure**: Unlike traditional neural networks that operate on grid-like data (e.g.
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