readme: ---
  thumbnail: "url to a thumbnail used in social sharing"
  tags:
  - graph neural networks
  license:
  - cc0-1.0
  ---
  
  ## Keras Implementation of Graph Attention Networks for Node Classification 🕸
  
  This repo contains the model and the notebook [to this Keras example on Graph Attention Networks for Node Classification](https://keras.io/examples/graph/gat_node_classification/).
  
  Full credits to: [Alexander Kensert](https://github.com/akensert)
  
  ## Background Information 
  Graph neural networks is the preferred neural network architecture for processing data structured as graphs (for example, social networks or molecule structures), yielding better results than fully-connected networks or convolutional networks.
  
  This tutorial implements a specific graph neural network known as a [Graph Attention Network (GAT)](https://arxiv.org/abs/1710.10903) to predict labels of scientific papers based on the papers they cite (using the [Cora dataset](https://linqs.soe.ucsc.edu/data)).
  
  References
  For more information on GAT, see the original paper [Graph Attention Networks](https://arxiv.org/abs/1710.10903) as well as [DGL's Graph Attention Networks](https://docs.dgl.ai/en/0.4.x/tutorials/models/1_gnn/9_gat.html) documentation.
  