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David Chapman

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#machine learning Preprint Sep 2026

RDDMPI: Residual Denoising Diffusion Model for Probabilistic Multivariate Time Series Imputation

This work proposes RDDMPI, a conditional residual diffusion framework that operates directly in residual space, and reformulates probabilistic imputation as a baseline-residual decomposition, where a pretrained model captures the dominant signal and a diffusion process models the residual uncertainty.

Ramiro Valdes Jara, David Chapman, Adam Meyers · 0 citations