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cs.LG2026
Jumping up and down: Denoiser diffusion models for discrete ordinal data
Yair Shenfeld, Ricardo Baptista, Stefano Peluchetti
Diffusion models are highly developed in continuous spaces for image and video domains. Recently, major advances have been made for discrete diffusion models for categorical data,…
cs.LG2026
Binomial flows: Denoising and flow matching for discrete ordinal data
Yair Shenfeld, Ricardo Baptista, Stefano Peluchetti
Flow-based generative modeling in continuous spaces exploit Tweedie's formula to express the denoiser (learned in training) as a score function (used in sampling). In contrast, thi…