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Jumping up and down: Denoiser diffusion models for discrete ordinal data

Shenfeld, Yair et al.
arXiv (All) · Papers
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machine-learningmethodology
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, specifically in the language domain. In contrast, diffusion models for discrete integer-valued data are less developed,
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