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Implementation of CIKM2020 -- Graph Prototypical Networks for Few-shot Learning on Attributed Networks

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Graph Prototypical Networks for Few-shot Learning on Attributed Networks (CIKM2020)

Graph Prototypical Networks (GPN)

This is the source code of paper "Graph Prototypical Networks for Few-shot Learning on Attributed Networks". The proposed framework

Requirements

python==3.6.6

torch==1.4.0

Usage

python train_gpn.py --shot 5 --way 5 --episodes 1000 --dataset dblp --dropout 0.5 --use_cuda

Citation

Please cite our paper if you use this code in your own work:

@inproceedings{ding2020graph,
  title={Graph prototypical networks for few-shot learning on attributed networks},
  author={Ding, Kaize and Wang, Jianling and Li, Jundong and Shu, Kai and Liu, Chenghao and Liu, Huan},
  booktitle={Proceedings of the 29th ACM International Conference on Information \& Knowledge Management},
  pages={295--304},
  year={2020}
}

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Implementation of CIKM2020 -- Graph Prototypical Networks for Few-shot Learning on Attributed Networks

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