Author

Martin J. Wainwright

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Preprint Aug 2026

The data geometry of masking diffusion: Certified-optimal schedules via unmasking growth complexity

We study masking diffusion for discrete sampling and introduce a path-resolved measure of data geometry called the \emph{unmasking growth complexity} ({\textsf{UGC}\xspace}). Its local increments directly control Kullback--Leibler (KL) discretization error, yielding a unified analysis of Bernoulli-subset and fixed-card...

Martin J. Wainwright · 6 citations · ⚡1

Jul 2026

Denoising growth complexity: Data geometry and certified schedules for diffusion sampling

It is shown how the $\mathsf{DGC}$ increments lead to a simple and explicit bound on the KL error of an Euler scheme applied to the stochastic innovations representation, thereby recovering and sharpening a range of existing diffusion-sampling guarantees, as well as giving new results.

Martin J. Wainwright · arXiv.org · 1 citation

#artificial intelligence Preprint Aug 2026

The information geometry of product-reference discrete diffusion: Interaction growth complexity and optimal scheduling

The aggregate IGC mass admits bounds in terms of total correlation and dual total correlation, thereby connecting the pathwise geometry to classical measures of multivariate dependence and connecting the pathwise geometry to classical measures of multivariate dependence.

Martin J. Wainwright · 0 citations