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https://github.com/shagunsodhani/pregel

Tensorflow implementation of Graph Convolutional Network
https://github.com/shagunsodhani/pregel

graph-convolutional-network tensorflow

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Tensorflow implementation of Graph Convolutional Network

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# pregel
Tensorflow implementation of Graph Convolutional Network

## Setup

* `sudo pip3 install -r requirements.txt`

## Run

* `python3 main.py -h` to view all the config parameters. Update the default parameters in the `main.py` file.
* `python3 main.py` to run the models.
* `tensorboard --logdir=run1: -port 6006` to run tensorboard and go to `http://localhost/6006`

## References

This work is an attempt to reproduce some of the works related to graph convolutional networks:

#### [Semi-Supervised Classification with Graph Convolutional Networks](https://arxiv.org/abs/1609.02907)

```
@article{kipf2016semi,
title={Semi-Supervised Classification with Graph Convolutional Networks},
author={Kipf, Thomas N and Welling, Max},
journal={arXiv preprint arXiv:1609.02907},
year={2016}
}
```

* [Author's implementation in Tensorflow](https://github.com/tkipf/gcn)
* [Author's implementation in Keras](https://github.com/tkipf/keras-gcn)
* [Author's implementation in PyTorch](https://github.com/tkipf/pygcn)

#### [Variational Graph Auto-Encoders](https://arxiv.org/abs/1611.07308)

```
@article{hamilton2017representation,
title={Representation Learning on Graphs: Methods and Applications},
author={Hamilton, William L and Ying, Rex and Leskovec, Jure},
journal={arXiv preprint arXiv:1709.05584},
year={2017}
}
```

* [Author's implementation in Tensorflow](https://github.com/tkipf/gae)