Bi-GCN
Official Implementation of CVPR 2021 Paper: Bi-GCN: Binary Graph Convolutional Network
Please cite our paper if you use this code in your own work:
@article{wang2020bi,
title={Bi-GCN: Binary Graph Convolutional Network},
author={Wang, Junfu and Wang, Yunhong and Yang, Zhen and Yang, Liang and Guo, Yuanfang},
journal={arXiv preprint arXiv:2010.07565},
year={2020}
}
Requirements
- torch==1.7.0
- torch_geometric==1.7.0
- scikit_learn
Run
Run the demo of Bi-GCN on Cora dataset by this command.
python transductive-bigcn.py --device 0
You can specify a dataset, set the layer number, or other hyper-parameters by setting the optional args.
python bi-gcn.py --gpu 0 --dataset Cora --layers 4
You can run the file inductive-gs-bignn.py
and inductive-ns-bignn.py
to get the results of binarized version of other GNNs, like inductive GCN, GraphSAGE, and GraphSAINT.
python inductive-ns-bignn.py --device 6 --model GraphSAGE --dataset Reddit --binarize
The shell script of the reported results in Table 2, 3 can be found in results.sh
.