Review for NeurIPS paper: Implicit Rank-Minimizing Autoencoder

Strengths: This paper is quite amazing. Just adding a few linear layers causes otherwise standard, deterministic autoencoders to learn interesting generative factors of a similar or possibly greater quality to VAEs. It's rare to see a simple idea that works very well, with many possible extensions. I think this result will be of wide interest to the community. The theoretical observation that gradient descent dynamics in deep linear networks finds low rank solutions is well established, but has not been put to practical use.