Code release for "Co-embedding of Nodes and Edges with Graph Neural Networks" (IEEE PAMI 2020) and "CensNet: Convolution with Edge-Node Switching in Graph Neural Networks" (IJCAI 2019)
- Python3
- Pytorch == 1.0.0 (with suitable CUDA and CuDNN version)
- Numpy
- argparse
- tqdm
The datasets (Cora, Citeseer and PubMed) are in GoogleDrive and BaiduPan (pw:frvg).
You need to move the dataset file into CensNet file.
You can run python train.py to train and evaluate.
If you use this code for you research, please consider citing:
@article{jiang2020co,
title={Co-embedding of Nodes and Edges with Graph Neural Networks},
author={Jiang, Xiaodong and Zhu, Ronghang and Ji, Pengsheng and Li, Sheng},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
year={2020},
publisher={IEEE}
}
@inproceedings{jiang2019censnet,
title={CensNet: Convolution with Edge-Node Switching in Graph Neural Networks.},
author={Jiang, Xiaodong and Ji, Pengsheng and Li, Sheng},
booktitle={IJCAI},
pages={2656--2662},
year={2019}
}
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