This repository provides a TensorFlow/Keras implementation of the Graph Attention Network (GAT) model from the 2018 ICLR paper by Veličković et al. The model uses attention mechanisms to aggregate features from neighboring nodes in a graph, enabling semi-supervised learning on graph-structured data. The implementation includes utilities for data loading and splitting, and was designed to work with citation datasets like Cora.