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Spanning Diffusion and Flow-based Posterior Sampling via Exact Gaussian Conditioning

Paper recorded by Signals 4 on 2026-10-09 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-09 on arXiv · recorded by Signals 4 on 2026-10-12

Category: cs.LG · 机器学习 · first seen 2026-10-12

Abstract

Flow-matching and diffusion models are increasingly used as priors for linear inverse problems, however, most methods are bespoke to one class of trajectory prior. Plug-and-play methods have been proposed, however these implicitly decorrelate the guided trajectory, resulting in broad priors that can struggle when data is sparse. This work proposes $β$-Flow: a general plug-and-play method indexed b

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#314 most recent of 749 cs.LG papers we have recorded · ↑ newer: Dream to Remember: Continual Steering of Generalist Robot Policies wit · ↓ older: CSF: Contextual Safety Filtering for Motion Generators
Cite this page: Spanning Diffusion and Flow-based Posterior Sampling via Exact Gaussian Conditioning: the #314 most recent of 749 cs.LG papers we have recorded (as of 2026-10-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/spanning-diffusion-and-flow-based-posterior-sampling-via-exact-gaussian-conditio.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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