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Deep latent variable models have seen recent success in many data domains.Lossless compression is an application of these models which, despite havingthe potential to be highly useful, has yet to be implemented in a practicalmanner. We present `Bits Back with ANS' (BB-ANS), a scheme to perform losslesscompression with latent variable models at a near optimal rate. We demonstratethis scheme by using it to compress the MNIST dataset with a variationalauto-encoder model (VAE), achieving compression rates superior to standardmethods with only a simple VAE. Given that the scheme is highly amenable toparallelization, we conclude that with a sufficiently high quality generativemodel this scheme could be used to achieve substantial improvements incompression rate with acceptable running time. We make our implementationavailable open source at https://github.com/bits-back/bits-back .

Practical Lossless Compression with Latent Variables using Bits Back Coding