Awesome
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}
}