Review for NeurIPS paper: Hierarchical Quantized Autoencoders

Weaknesses: I believe the contributions might be a bit overblown. In particular, in the first bullet point the authors mention an "analysis as to why probabilistic quantized hierarchies are particularly well-suited to optimising the perception-rate tradeoff when performing extreme lossy compression", but there doesn't seem to be a thorough and conclusive analysis on this matter. Points (2, 3) and (4, 5) are in my opinion spread too thin and should be combined. I find the model description somewhat lacking in clarity. I think everything would be much more understandable with a simple, but more structured, exposition (with equations) of the model, and possibly also of VQ-VAE, as this work heavily builds on it.