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PyTorch implementation for ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning accepted by ICML 2022.
ProGCL-weight:
python train.py --device cuda:0 --dataset Amazon-Computers --param local:amazon-computers.json --mode weight
ProGCL-mix:
python train.py --device cuda:0 --dataset Amazon-Computers --param local:amazon-computers.json --mode mix
@inproceedings{xia2022progcl,
title={ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning},
author={Xia, Jun and Wu, Lirong and Wang, Ge and Li, Stan Z.},
booktitle={International conference on machine learning},
year={2022},
organization={PMLR}
}
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