Deep Learning Approach to Data Compression

Worked in a related space.  Good high level description of what was done, but this is by its nature technical

In Berkeley AI Research  (BAIR) :

A Deep Learning Approach to Data Compression
By Friso Kingma,    Sep 19, 2019

The BAIR Blog

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The BAIR Blog provides an accessible, general-audience medium for BAIR researchers to communicate research findings, perspectives on the field, and various updates. Posts are written by students, post-docs, and faculty in BAIR, and are intended to provide relevant and timely discussion of research findings and results, both to experts and the general audience. Posts on a variety of topics studied at BAIR will appear approximately once every two weeks. ... 

We introduce Bit-Swap, a scalable and effective lossless data compression technique based on deep learning. It extends previous work on practical compression with latent variable models, based on bits-back coding and asymmetric numeral systems. In our experiments Bit-Swap is able to beat benchmark compressors on a highly diverse collection of images. We’re releasing code for the method and optimized models such that people can explore and advance this line of modern compression ideas. We also release a demo and a pre-trained model for Bit-Swap image compression and decompression on your own image. See the end of the post for a talk that covers how bits-back coding and Bit-Swap works. .... "