Keras-based implementation of graph convolutional networks for semi-supervised classification.
Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
For a high-level explanation, have a look at our blog post:
Thomas Kipf, Graph Convolutional Networks (2016)
NOTE: This code is not intended to reproduce the experiments from the paper as the initialization scheme, dropout scheme, and dataset splits differ from the original implementation in TensorFlow: https://github.com/tkipf/gcn
python setup.py install
- keras (1.0.9 or higher)
- TensorFlow or Theano
python train.py
Sen et al., Collective Classification in Network Data, AI Magazine 2008
Please cite our paper if you use this code in your own work:
@inproceedings{kipf2017semi,
title={Semi-Supervised Classification with Graph Convolutional Networks},
author={Kipf, Thomas N. and Welling, Max},
booktitle={International Conference on Learning Representations (ICLR)},
year={2017}
}