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Stefan Oberdorster

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#machine learning Preprint Sep 2026

Local Geometric Mixing via Dobrushin Contraction with Applications to Diffusion Path Monte Carlo and the Proximal Sampler

This work establishes and discusses local geometric mixing bounds through Dobrushin contraction, and applies this approach to Diffusion Path Monte Carlo, a recently proposed Markov chain Monte Carlo method aimed at leveraging advances in score-based modeling.

Stefan Oberdorster · 0 citations

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