Authors
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow
Publication date
2015/11/18
Journal
arXiv preprint arXiv:1511.05644
Description
Abstract: In this paper we propose a new method for regularizing autoencoders by imposing
an arbitrary prior on the latent representation of the autoencoder. Our method, named"
adversarial autoencoder", uses the recently proposed generative adversarial networks
(GAN) in order to match the aggregated posterior of the hidden code vector of the
autoencoder with an arbitrary prior. Matching the aggregated posterior to the prior ensures
that there are no" holes" in the prior, and generating from any part of prior space results in ...
Total citations
201610
Scholar articles
A Makhzani, J Shlens, N Jaitly, I Goodfellow - arXiv preprint arXiv:1511.05644, 2015