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[ACM MM 2024] An official source code for paper "GraphLearner:Graph Node Clustering with Fully Learnable Augmentation".

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GraphLearner:Graph Node Clustering with Fully Learnable Augmentation

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An official source code for paper GraphLearner:Graph Node Clustering with Fully Learnable Augmentation, accepted by ACM MM 24. Any communications or issues are welcomed. Please contact xihong_edu@163.com. If you find this repository useful to your research or work, it is really appreciate to star this repository. ❤️


Overview

Illustration of GraphLearner:Graph Node Clustering with Fully Learnable Augmentation.

Requirements

The proposed GraphLearner is implemented with python 3.8.8 on a NVIDIA 3090 Ti GPU.

Python package information is summarized in requirements.txt:

  • torch==1.8.0
  • tqdm==4.61.2
  • numpy==1.21.0
  • tensorboard==2.8.0

Quick Start

python train.py 

Citation

If you use code or datasets in this repository for your research, please cite our paper.

@inproceedings{GraphLearner,
  title={Graphlearner: Graph node clustering with fully learnable augmentation},
  author={Yang, Xihong and Min, Erxue and Liang, Ke and Liu, Yue and Wang, Siwei and Zhou, Sihang and Wu, Huijun and Liu, Xinwang and Zhu, En},
  booktitle={Proceedings of the 32nd ACM International Conference on Multimedia},
  pages={5517--5526},
  year={2024}
}

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[ACM MM 2024] An official source code for paper "GraphLearner:Graph Node Clustering with Fully Learnable Augmentation".

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