Code for the paper Population Matching Discrepancy and Applications in Deep Learning.
Make sure that you have valid c++11 and cuda compilers.
git clone [email protected]:cjf00000/pmd.git
cd pmd
pip install --upgrade pip
pip install cython numpy tensorflow scipy matplotlib scikit-image scikit-learn seaborn
pip install -e .
Download the data
cd domain_adaptation
wget -O data.tar.gz https://github.com/cjf00000/pmd-data/blob/master/data.tar.gz?raw=true
tar xzvf data.tar.gz
See config.pmd or config.mmd for the training recipes.
The scripts will automatically download MNIST and CIFAR10 datasets.
Running:
cd generative-model
mkdir data
configs/mnist_pmd_fc
The images will be generated in the result directory.
If you find the code is useful, please cite our paper!
@inproceedings{chen2017population,
title={Population Matching Discrepancy and Applications in Deep Learning},
author={Chen, Jianfei and Chongxuan, LI and Ru, Yizhong and Zhu, Jun},
booktitle={Advances in Neural Information Processing Systems},
pages={6263--6275},
year={2017}
}