A timeline of sampling methods of diffusion models (opens in new tab)

When approaching the methods used in de-novo protein design, one is quickly confronted with a plethora of overlapping formulations of what looks superficially like “the same thing”. One paper trains an ϵ\boldsymbol{\epsilon}-prediction network with a simple MSE loss; another trains a score network with a stochastic-differential-equation justification; a third trains a clean-data predictor under yet another schedule. Each formulation carries its own notation, its own variance schedule, and its...