/Graph-Attention-Net

A TensorFlow 2 implementation of Graph Attention Networks (GAT)

Primary LanguagePythonMIT LicenseMIT

Graph Attention Networks

A TensorFlow 2 implementation of Graph Attention Networks for classification of nodes from the paper, Graph Attention Networks (Veličković et al., ICLR 2018).

This is my attempt at trying to understand and recreate the neural network from from the paper. You can find the official implementation here: https://github.com/PetarV-/GAT

Requirements

  • tensorflow 2
  • networkx
  • numpy
  • scikit-learn

Run

To train and test the network with the CORA dataset.

python train.py

Cite

Please cite the original paper if you use this code in your own work:

@article{
  velickovic2018graph,
  title="{Graph Attention Networks}",
  author={Veli{\v{c}}kovi{\'{c}}, Petar and Cucurull, Guillem and Casanova, Arantxa and Romero, Adriana and Li{\`{o}}, Pietro and Bengio, Yoshua},
  journal={International Conference on Learning Representations},
  year={2018},
  url={https://openreview.net/forum?id=rJXMpikCZ},
  note={accepted as poster},
}