arXiv Machine Learning By Jinshu Huang, Yiming Jiang, Chunlin Wu

From Score Learning to Discretized Sampling: An End-to-End Generalization Analysis of Diffusion Models

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arXiv:2607. 23226v1 Announce Type: new Abstract: Despite the empirical success of score-based diffusion models, a complete theoretical understanding of how finite-sample learning, network parameterization, and numerical discretization jointly dictate generative quality remains underdeveloped.

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arXiv Machine Learning
Jul 17

The Effect of Stochasticity in Score-Based Diffusion Sampling: a KL Divergence Analysis

arXiv:2506. 11378v3 Announce Type: replace Abstract: Sampling in score-based diffusion models can be performed by solving either a reverse-time stochastic differential equation (SDE) parameterized by an arbitrary stochasticity function or a probability flow ODE, corresponding to setting this stochasticity function to zero.

By Bernardo P. Schaeffer, Ricardo M. S. Rosa, Glauco Valle