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Apr, 2023
用Lookahead Diffusion概率模型改进均值估计
Lookahead Diffusion Probabilistic Models for Refining Mean Estimation
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Guoqiang Zhang, Niwa Kenta, W. Bastiaan Kleijn
TL;DR
本研究提出一种基于深度神经网络和先行扩散概率模型的方法,通过在反向过程中的外推方法进行修正,提高了条件高斯分布均值的估计精度,进而提高了FID得分。
Abstract
We propose
lookahead diffusion probabilistic models
(LA-DPMs) to exploit the correlation in the outputs of the
deep neural networks
(DNNs) over subsequent timesteps in diffusion probabilistic models (DPMs) to ref
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