Definition
A graph is a fundamental data structure in AI comprising vertices (nodes) and edges (links) that denote relationships. Graph Neural Networks (GNNs) leverage this structure to perform learning on non-Euclidean data, such as social networks or molecular structures. Unlike grid-based data processed by CNNs, graphs allow for irregular connectivity and variable sizes. Graphs are essential for knowledge representation, reasoning, and modeling complex interactions where the relationship between items is as important as the items themselves.
Summary
A mathematical structure consisting of nodes connected by edges, used to represent relationships between entities.
Key Concepts
- Nodes/Vertices
- Edges
- Adjacency Matrix
- Topology
Use Cases
- Knowledge Graphs
- Social Network Analysis
- Molecular Property Prediction