AI RESEARCH
Diffusion Models for Solving Inverse Problems via Posterior Sampling with Piecewise Guidance
arXiv CS.LG
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ArXi:2507.18654v2 Announce Type: replace Diffusion models are powerful tools for sampling from high-dimensional distributions by progressively transforming pure noise into structured data through a denoising process. When equipped with a guidance mechanism, these models can also generate samples from conditional distributions. In this paper, a novel diffusion-based framework is