Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables

05/16/2019
by   Friso H. Kingma, et al.
11

The bits-back argument suggests that latent variable models can be turned into lossless compression schemes. Translating the bits-back argument into efficient and practical lossless compression schemes for general latent variable models, however, is still an open problem. Bits-Back with Asymmetric Numeral Systems (BB-ANS), recently proposed by Townsend et al. (2019), makes bits-back coding practically feasible for latent variable models with one latent layer, but it is inefficient for hierarchical latent variable models. In this paper we propose Bit-Swap, a new compression scheme that generalizes BB-ANS and achieves strictly better compression rates for hierarchical latent variable models with Markov chain structure. Through experiments we verify that Bit-Swap results in lossless compression rates that are empirically superior to existing techniques. Our implementation is available at https://github.com/fhkingma/bitswap.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/15/2019

Practical Lossless Compression with Latent Variables using Bits Back Coding

Deep latent variable models have seen recent success in many data domain...
research
02/22/2021

Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding

Latent variable models have been successfully applied in lossless compre...
research
01/05/2022

Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective

Entropy coding is the backbone data compression. Novel machine-learning ...
research
02/18/2020

Variable-Bitrate Neural Compression via Bayesian Arithmetic Coding

Deep Bayesian latent variable models have enabled new approaches to both...
research
06/07/2020

Improving Inference for Neural Image Compression

We consider the problem of lossy image compression with deep latent vari...
research
12/20/2019

HiLLoC: Lossless Image Compression with Hierarchical Latent Variable Models

We make the following striking observation: fully convolutional VAE mode...
research
11/23/2021

Lossless Compression with Probabilistic Circuits

Despite extensive progress on image generation, deep generative models a...

Please sign up or login with your details

Forgot password? Click here to reset