A PyTorch implementation of Transfer Learning with Dynamic Distribution Adaptation which has published on ACM Transactions on Intelligent Systems and Technology.
This is also called DDAN (Deep Dynamic Adaptation Network).
Matlab version is HERE.
- python 3
- pytorch 1.x
- Numpy, scikit-learn
- You can download Office31 dataset here. Also, other datasets are supported in here.
- Run
python main.py --src dslr --tar amazon --batch_size 32.
Note that for tasks D-A and W-A, setting epochs = 800 or larger could achieve better performance.
Wang J, Chen Y, Feng W, et al. Transfer learning with dynamic distribution adaptation[J].
ACM Transactions on Intelligent Systems and Technology (TIST), 2020, 11(1): 1-25.
or in bibtex style:
@article{wang2020transfer,
title={Transfer learning with dynamic distribution adaptation},
author={Wang, Jindong and Chen, Yiqiang and Feng, Wenjie and Yu, Han and Huang, Meiyu and Yang, Qiang},
journal={ACM Transactions on Intelligent Systems and Technology (TIST)},
volume={11},
number={1},
pages={1--25},
year={2020},
publisher={ACM New York, NY, USA}
}