Formulating Discrete Probability Flow Through Optimal Transport

Neural Information Processing Systems 

Continuous diffusion models are commonly acknowledged to display a deterministic probability flow, whereas discrete diffusion models do not. In this paper, we aim to establish the fundamental theory for the probability flow of discrete diffusion models. Specifically, we first prove that the continuous probability flow is the Monge optimal transport map under certain conditions, and also present an equivalent evidence for discrete cases.

Similar Docs  Excel Report  more

TitleSimilaritySource
None found