Graph Attention Networks: Adaptive Feature Aggregation via Self-Attention
Graph Attention Networks (GATs) introduce attention mechanisms into graph neural architectures to enable adaptive weighting of neighboring nodes. Proposed by Veličković et al. in 2017, this architecture computes importance coefficients between connected nodes through masked self-attention layers, al...