Official codebase of our ICCV paper "Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation"
We use Normalized Wasserstein measure for two applications
- Domain adaptation under covariate and label shift
- Generative modeling
Please refer to the README files on the respective folders on how to run the code.
If you use this code for your research, please cite
@InProceedings{Balaji_2019_ICCV,
author = {Balaji, Yogesh and Chellappa, Rama and Feizi, Soheil},
title = {Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}