/GCC

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

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GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training.

GCC is a contrastive learning framework that implements unsupervised structural graph representation pre-training and achieves state-of-the-art on 10 datasets on 3 graph mining tasks.

Installation

See INSTALL.md.

Quick Start

See GETTING_STARTED.md.

Citing GCC

If you use GCC in your research or wish to refer to the baseline results, please use the following BibTeX.

@article{qiu2020gcc,
  title={GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training},
  author={Qiu, Jiezhong and Chen, Qibin and Dong, yuxiao and Zhang, Jing and Yang, Hongxia and Ding, Ming and Wang, Kuansan and Tang, Jie},
  journal={arXiv preprint arXiv:2006.09963},
  year={2020}
}