Spectral clustering is a method used to group data points into clusters based on how closely they are connected to each other. It works by representing the data as a graph, where each point is a node and edges show how similar points are. The technique uses mathematics from linear algebra, specifically eigenvalues and eigenvectors,…
Graph Attention Networks, or GATs, are a type of neural network designed to work with data structured as graphs. Unlike traditional neural networks that process fixed-size data like images or text, GATs can handle nodes and their connections directly. They use an attention mechanism to decide which neighbouring nodes are most important when making predictions…
A Directed Acyclic Graph, or DAG, is a collection of points, called nodes, connected by arrows, called edges, where each arrow has a direction. In a DAG, you cannot start at one node and follow the arrows in a way that leads you back to the starting point. This structure makes DAGs useful for representing…
A knowledge graph is a way of organising information that connects facts and concepts together, showing how they relate to each other. It uses nodes to represent things like people, places or ideas, and links to show the relationships between them. This makes it easier for computers to understand and use complex information, helping with…