Skip to content

Pytorch implementation of Semi-Supervised Disentanglement of Class-Related and Class-Independent Factors in VAE paper

License

Notifications You must be signed in to change notification settings

sinahmr/parted-vae

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PartedVAE

Pytorch implementation of Semi-Supervised Disentanglement of Class-Related and Class-Independent Factors in VAE (PartedVAE).

This repository's structure is based on the joint-vae repository.

Usage

Use main.py to train the model. Add needed tests and evaluations at the end.

Citing

If you find our work useful in your research, please cite using:

@article{hajimiri2021semi,
  title={Semi-Supervised Disentanglement of Class-Related and Class-Independent Factors in VAE},
  author={Hajimiri, Sina and Lotfi, Aryo and Soleymani Baghshah, Mahdieh},
  journal={arXiv preprint arXiv:2102.00892},
  year={2021}
}

License

MIT

About

Pytorch implementation of Semi-Supervised Disentanglement of Class-Related and Class-Independent Factors in VAE paper

Topics

Resources

License

Stars

Watchers

Forks

Languages