401 citations · 1.3k across the 12 of their papers we have counts for
3 papers · 1 filter
Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer
David Berthelot, Colin Raffel, Aurko Roy +1
Autoencoders provide a powerful framework for learning compressed representations by encoding all of the information needed to reconstruct a data point in a latent code. In some ca…
Theory and Experiments on Vector Quantized Autoencoders
Aurko Roy, Ashish Vaswani, Arvind Neelakantan +1
Deep neural networks with discrete latent variables offer the promise of better symbolic reasoning, and learning abstractions that are more useful to new tasks. There has been a su…
Fast Decoding in Sequence Models using Discrete Latent Variables
Łukasz Kaiser, Aurko Roy, Ashish Vaswani +4
Autoregressive sequence models based on deep neural networks, such as RNNs, Wavenet and the Transformer attain state-of-the-art results on many tasks. However, they are difficult t…