A New Look on Diffusion Times for Score-based Generative Models
Abstract
Score-based diffusion models map noise into data using stochastic differential equations. While current practice advocates for a large T to ensure closeness to steady state, a smaller value of T should be preferred for a better approximation of the score-matching objective and computational efficiency. We conjecture, contrary to current belief and corroborated by numerical evidence, that the optimal diffusion times are smaller than current practice.
Domains
Computer Aided Engineering
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