Graphs, recommendations, and time series · MLD-0486
Graph attention network
A graph neural architecture that learns weights for neighboring nodes during aggregation.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Weight different neighbors by their relevance.
Original caveat
Attention weights alone are not a complete causal explanation.
Context and aliases
Level: Intermediate. Stages: Architecture · Data · Training · Inference.
Tags: ML · DL · Graph ML.
Aliases: GAT.
Related concepts
Concepts linking here
Original references
- PyTorch Geometric documentation ↗ · Consulted
- scikit-learn User Guide ↗ · Consulted
- statsmodels: time series analysis ↗ · Reference link
- Original reference URL ↗