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First-Order Stationarity of Reverse Diffusions

Paper recorded by Signals 4 on 2026-09-25 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-25 on arXiv · recorded by Signals 4 on 2026-09-28

Category: cs.LG · 机器学习 · first seen 2026-09-28

Abstract

Recent literature has shown a strong connection between optimization and sampling. We develop the corresponding first-order theory for diffusion models. First, the SDE-based reverse-time flows of overdamped and underdamped Langevin diffusions contract relative Fisher divergences at explicit exponential rates whenever the stationary potential of the forward process is strongly convex---a condition

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#2 most recent of 310 cs.LG papers we have recorded · ↑ newer: Gap-free Differentially Private PCA for Gaussian Data · ↓ older: User Model Extraction via Belief Self-Distillation
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