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In posterior sampling with diffusion models, SMC treats each denoising step of the diffusion process as an intermediate distribution and maintains a set of weighted particles to approximate these distributions; at each step the particles are propagated according to the prior score, then reweighted according to the observation likelihood, and resampling is used to avoid weight degeneracy.
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11/3/2026
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UnverifiedDuring generation, SMC maintains a set of weighted candidate sequences (particles), reweighting and resampling them at each step according to the potential functions.75% similarVerifiedThe denoising sampling process of a diffusion model can be regarded as the solution of a stochastic differential equation, comprising a deterministic drift term and a stochastic diffusion term.74% similarVerified扩散模型的核心原理分为前向扩散过程（逐步添加高斯噪声）和反向去噪过程（从噪声中还原图像）两个阶段73% similarUnverified在扩散模型中，UNet的任务是在每一步采样中预测并去除潜空间中的噪声，经多步迭代还原图像73% similarVerified扩散模型是一类基于马尔可夫链的生成模型，核心思想是通过前向加噪和反向去噪来捕捉数据分布73% similar
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