Mutual variational inference: An indirect variational inference approach for unsupervised domain adaptation
This is the Python+PyTorch code to reproduce the results of domain adaptation in image classification in paper 'Mutual variational inference: An indirect variational inference approach for unsupervised domain adaptation'.
Requirements
- Platform : Linux
- Computing Environment:
- CUDA 10.1
- PyTorch
- Packages:
pandas, numpy, scipy, argparse, tqdm
. - Hardware : Nvidia GPU
Run the code
- Download ResNet-50 pretrained model and place it under
model/
. - Download necessary DA datasets and place it under
data/
. - Run bash file
batchrun.sh
Citation
Please cite our paper if you found it usefull.
@article{chen2021mutual,
title={Mutual variational inference: An indirect variational inference approach for unsupervised domain adaptation},
author={Chen, Jiahong and Wang, Jing and de Silva, Clarence W},
journal={IEEE Transactions on Cybernetics},
year={2022},
volume={52},
number={11},
pages={11491-11503},
doi={10.1109/TCYB.2021.3107292}
}