wehub-resource-sync
29 lines
772 B
Markdown
29 lines
772 B
Markdown
# Learning Deep Generative Models of Graphs
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This is an implementation of [Learning Deep Generative Models of Graphs](https://arxiv.org/pdf/1803.03324.pdf) by
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Yujia Li, Oriol Vinyals, Chris Dyer, Razvan Pascanu, Peter Battaglia.
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For molecule generation, see
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[DGL-LifeSci](https://github.com/awslabs/dgl-lifesci/tree/master/examples/generative_models/dgmg).
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## Dependencies
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- Python 3.5.2
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- [Pytorch 0.4.1](https://pytorch.org/)
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- [Matplotlib 2.2.2](https://matplotlib.org/)
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## Usage
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`python3 main.py`
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## Performance
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90% accuracy for cycles compared with 84% accuracy reported in the original paper.
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## Speed
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On AWS p3.2x instance (w/ V100), one epoch takes ~526s.
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## Acknowledgement
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We would like to thank Yujia Li for providing details on the implementation.
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