PyTorch implementation for paper Decoupled Contrastive Multi-View Clustering with High-Order Random Walks (AAAI 2024)

Requirements

pytorch>=1.13.0

numpy>=1.23.4

scikit-learn>=0.0.post1

munkres>=1.1.4

Datasets

You could find the dataset we used in the paper at Google Drive.

Training

The hyper-parameters, the training options are defined in the configure file.

main_train.py --config_file=config/Scene15.yaml

main_train.py --config_file=config/Caltech101.yaml

Reference

If you find our work useful in your research, please consider citing:

@article{lu2024decoupled,
  title={Decoupled Contrastive Multi-view Clustering with High-order Random Walks},
  author={Lu, Yiding and Lin, Yijie and Yang, Mouxing and Peng, Dezhong and Hu, Peng and Peng, Xi},
  journal={Thirty-Eighth AAAI Conference on Artificial Intelligence},
  year={2024}
}