I read research papers and write them up the way I wish they had been explained to me the first time: the question before the notation, a picture wherever a picture helps, and code short enough to read in one sitting.

The main project here is a growing library of diffusion model papers — starting with the 2020 paper that made the whole approach work, and following the chain of ideas forward to the systems behind today’s image and video generators.

Two rules I try to hold myself to:

  1. No hand-waving. If I cannot explain why a step is there, I say so rather than papering over it.
  2. Say what the paper got wrong. The limitations are the interesting part — they are what the next paper is about.

Corrections, arguments, and requests for papers to cover are all welcome: open an issue.

Elsewhere: GitHub.