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Discrete Autoencoders for Sequence Models

Lukasz Kaiser
Samy Bengio
arXiv (2018)


The contributions of this paper are: * A discretization technique that works well without any extra losses or parameters to tune. * A way to measure performance of autoencoders for sequence models (and baselines). * An improved way to sample from sequence models (trained with an autoencoder part).

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