Binomial Flows: Denoising and flow matching for discrete ordinal data

Shenfeld presents binomial flows, a discrete analogue of Tweedie-based diffusion for ordinal, non-negative integer data. The method pairs binomial thinning for noising with a Poisson-type continuous-time Markov chain whose rate is expressed through a learned denoiser, enabling training with MSE, sampling, and exact likelihood estimation. Results include the best reported CIFAR-10 FID among ordinal discrete diffusion models, obtained by adapting the EDM framework.