Highly Technical Reference Page: "the GAN Zoo" and "Delving deep into Generative Adversarial Networks (GANs)"

Much like what happened with the Advanced Matrix Factorization Jungle, here is a new Highly Technical Reference page, on a subject of increased interest that is difficult to follow for even a specialist: GANs. 

If you wonder what GANs are, take a look at the tutorial on Generative Adversarial Networks by Ian Goodfellow (and his NIPS slides) or John Glover's entry last August on the subject 'with TF code).

Avinash Hindupur who is behind deephunt.in recently listed the log series of GANs techniques in the GAN Zoo. From the page: 

Every week, new papers on Generative Adversarial Networks (GAN) are coming out and it’s hard to keep track of them all, not to mention the incredibly creative ways in which researchers are naming these GANs! You can read more about GANs in this Generative Models post by OpenAI or this overview tutorial in KDNuggets.

Avinash also mentions that the list can be expanded: 

You can visit the Github repository to add more links via pull requests or create an issue to lemme know something I missed or to start a discussion.

The subject is so hot that there is an earlier and somewhat more complete page on the subject
Delving deep into Generative Adversarial Networks (GANs) by Grigorios Kalliatakis

A curated list of state-of-the-art publications and resources about Generative Adversarial Networks (GANs) and their applications.....

Contributions are welcome !! If you have any suggestions (missing or new papers, missing repos or typos) you can pull a request or start a discussion.

The blog post introducing the page is here.


Both pages are added to the Highly Technical Reference page

Join the CompressiveSensing subreddit or the Google+ Community or the Facebook page and post there !

Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.