Skip to content

ICLR 2018 Reproducibility Challenge: Paper - "Twin Networks: Matching the Future for Sequence Generation"

Notifications You must be signed in to change notification settings

ap229997/Twin-Networks-for-Sequence-Generation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

28 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Twin-Networks-for-Sequence-Generation

PyTorch implementation for ICLR 2018 accepted paper Twin Networks: Matching the Future for Sequence Generation [pdf] for verifying the results for image captioning on MSCOCO dataset and pixel-by-pixel generation on MNIST.

An analysis of the paper and the reproducibility results on both the datasets are provided in Reproducibility_Report.pdf.

The implementation details are provided in ImageCaptioningCOCO and SequentialMNIST.

Citation

If you find this code useful, please consider citing the original work by authors:

@inproceedings{Serdyuk2017TwinNM,
  title={Twin Networks: Matching the Future for Sequence Generation},
  author={Dmitriy Serdyuk and Nan Rosemary Ke and Alessandro Sordoni and Adam Trischler and Chris Pal and Yoshua Bengio},
  year={2017}
}

About

ICLR 2018 Reproducibility Challenge: Paper - "Twin Networks: Matching the Future for Sequence Generation"

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published