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Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial
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This is an expository article on the score-based diffusion models, with a particular focus on the formulation via stochastic differential equations (SDE). After a gentle introduction, we discuss the two pillars in the diffusion modeling -- sampling and score matching, which encompass the SDE/ODE sampling, score matching efficiency, the consistency models, and reinforcement learning. Short proofs are given to illustrate the main idea of the stated results. The article is primarily a technical introduction to the field, and practitioners may also find some analysis useful in designing new models or algorithms.
Forward citations
Cited by 4 Pith papers
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Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models
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