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Graphite: Iterative Generative Modeling of Graphs

Source code for our paper "Graphite: Iterative Generative Modeling of Graphs".

If you find it helpful, please consider citing our paper.

@article{grover2018iterative,
  title={Graphite: Iterative Generative Modeling of Graphs},
  author={Grover, Aditya and Zweig, Aaron and Ermon, Stefano},
  journal={arXiv preprint arXiv:1803.10459},
  year={2018}
}

Requirements

  1. python 2.7
  2. Tensorflow
  3. Networkx 1.11

Training

python train.py --epochs 500 --model feedback --edge_dropout 0.5 --learning_rate 0.01 --autoregressive_scalar 0.5

This code was built on top of a graph autoencoder (GAE) implementation available here.

If you have any questions, feel free to contact adityag@cs.stanford.edu or azweig@cs.stanford.edu.

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