A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Jie Gui
Dear all,
This paper is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
Paper link: https://github.com/guijiejie/guijiejie.github.io/blob/master/TKDE3130191.pdf
Supplementary material link: https://github.com/guijiejie/guijiejie.github.io/blob/master/GAN_TKDE_Supp.pdf
If you have any questions, feel free to contact the author. Thanks for reading.
Best wishes!
Jie
Dianbo liu
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Thomas Dietterich
This is a good question. When we created ML-News, we said “This group serves as a forum for notices and announcements of interest to the machine learning community. This includes events, calls for papers, employment-related announcements, etc.”
I share Dianbo Liu’s concern that if lots of people advertised papers here, it would be overwhelming. Twitter or Mastodon seem to be better places for that purpose. But this particular paper is an overview, and so it is perhaps “of interest to the machine learning community” more than most papers.
--Tom
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