Denoising Diffusion Probabilistic Models
PulseAugur coverage of Denoising Diffusion Probabilistic Models — every cluster mentioning Denoising Diffusion Probabilistic Models across labs, papers, and developer communities, ranked by signal.
2 天有情绪数据
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新的高斯混合模型提高了 DDIM 采样质量
研究人员开发了一种新方法来改进去噪扩散隐式模型 (DDIM) 的采样过程。他们的方法利用高斯混合模型 (GMM) 作为反向转移算子，该算子匹配 DDPM 前向边际的一阶和二阶中心矩。该技术已被证明能够生成与原始 DDIM 相当或更高质量的样本，尤其是在使用少量采样步数的情况下。
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New research links Föllmer processes to DDPMs, improving sampling efficiency
Researchers have explored the connection between Föllmer processes and denoising diffusion probabilistic models (DDPMs), finding that discretizing Föllmer processes can yield optimal hyper-parameter settings for DDPM sa…
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ExpoCM framework reconstructs HDR images faster
Researchers have developed ExpoCM, a new framework for reconstructing high dynamic range (HDR) images from single low dynamic range inputs. This method addresses the challenges of detail loss in over-exposed and noise i…