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GRAN

This is the official PyTorch implementation of Efficient Graph Generation with Graph Recurrent Attention Networks as described in the following NeurIPS 2019 paper:

@inproceedings{liao2019gran,
  title={Efficient Graph Generation with Graph Recurrent Attention Networks}, 
  author={Liao, Renjie and Li, Yujia and Song, Yang and Wang, Shenlong and Nash, Charlie and Hamilton, William L. and Duvenaud, David and Urtasun, Raquel and Zemel, Richard}, 
  booktitle={NeurIPS},
  year={2019}
}

Visualization

Generation of GRAN per step:

Overall generation process:

<img src="http://www.cs.toronto.edu/~rjliao/imgs/gran_generation.gif" height="400px" width="550px" />

Dependencies

Python 3, PyTorch(1.2.0)

Other dependencies can be installed via

pip install -r requirements.txt

Run Demos

Train

Note:

Test

Note:

Trained Models

Sampled Graphs from GRAN

Cite

Please cite our paper if you use this code in your research work.

Questions/Bugs

Please submit a Github issue or contact rjliao@cs.toronto.edu if you have any questions or find any bugs.