[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

Related tags

Deep Learning graph-convolutional-networks self-supervision graph-neural-networks self-supervised-learning
Overview

When Does Self-Supervision Help Graph Convolutional Networks?

PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks? [appendix]

Yuning You*, Tianlong Chen*, Zhangyang Wang, Yang Shen

In ICML 2020.

Overview

Properly designed multi-task self-supervision benefits GCNs in gaining more generalizability and robustness. In this repository we verify it through performing experiments on several GCN architectures with three designed self-supervised tasks: node clustering, graph partitioning and graph completion.

Dependencies

Please setup the environment following Section 3 (Setup Python environment for GPU) in this instruction, and then install the dependencies related to graph partitioning with the following commands:

sudo apt-get install libmetis-dev
pip install METIS==0.2a.4

Experiments

Citation

If you use this code for you research, please cite our paper.

@article{you2020does,
  title={When Does Self-Supervision Help Graph Convolutional Networks?},
  author={You, Yuning and Chen, Tianlong and Wang, Zhangyang and Shen, Yang},
  journal={Proceedings of machine learning research},
  volume={119},
  pages={10871--10880},
  year={2020}
}
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Comments
  • what is the mean of cluster_labels?

    what is the mean of cluster_labels?

    Hello: Thanks for your good jobs, but I do not know how can we obtain the datasets in folder clustrer_labels? what is the difference between ss_lables and labels?

    thank you!

    opened by cquzys 2
Owner
Shen Lab at Texas A&M University
Shen Lab at Texas A&M University
GitHub https://arxiv.org/abs/2006.09136
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