“加不同尺度噪声扰动数据”这个策略其实之前的很多工作中都有用到,其中和 score-based model 比较相关的是 diffusion probabilistic model[^7]。它是一种 hierarchical latent variable model,基于 evidence lower bound (ELBO) 进行训练,通过学习一个变分解码器以逆转将数据扰动为噪声的离散扩散过程,从而生成新样本。
在一文解释 Diffusion Model (一) 理论推导中从DDPM的角度解释了DM。这篇文章将提供一个全新的视角。 为了和文献一致,这里采用sθ(x,t)来表示神经网络的预测值,而不是fθ(x,t)。为了简化符号,用∇logpθ(x) 表示∇xlogpθ(x)。同时你需要知道 p(x;θ) 等价于 pθ(x)。 一开始不要步子...
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扩散模型和score-based模型的交汇发展始于2015年的diffusion probabilistic model，后来DDPM揭示了两者之间的内在联系，使得算法路径得以统一。宋飏博士的研究不仅推动了生成模型的发展，还展示了它们在数学上的统一性。
【研2基本功 Score-based Diffusion 1】手搓Diffusion SDE,数学is all you need 5.6万播放 大白话AI | 图像生成模型DDPM | 扩散模型 | 生成模型 | 概率扩散去噪生成模型 12.7万播放 【博士Vlog】2024最新模型Mamba详解,Transformer已死,你想知道的都在这里了! 12.3万播放 【中英双语】ChatGPT背后的数学原理是什么...
In this paper, we propose a novel approach using Stochastic Differential Equations based diffusion models to address multiplicative noise. We demonstrate that multiplicative noise can be effectively modeled as a Geometric Brownian Motion process in the logarithmic domain. Utilizing the Fokker-Planck ...
in our paper, this codebase also re-implements many previous score-based models in one place, includingNCSNfromGenerative Modeling by Estimating Gradients of the Data Distribution,NCSNv2fromImproved Techniques for Training Score-Based Generative Models, andDDPMfromDenoising Diffusion Probabilistic Models....
Based on the reduced diffusion mechanism for producing Forbush decreases (Fds) in the heliosphere, we constructed a three-dimensional (3D) diffusion barrie... Xi,Luo,Marius,... - 《Astrophysical Journal》 被引量: 2发表: 2017年 Based on ARCGIS-SDE Spatial Evolution Trend of Industrial Clusters...
Maxwellian plasma and arbitrary distribution function of background plasma have been considered.The adoption of the implicit midpoint method guarantees exactly the energy conservation for the diffusion term and thus improves the numerical stability compared with conventional Runge-Kutta methods.ISSDE is ...
in our paper, this codebase also re-implements many previous score-based models in one place, includingNCSNfromGenerative Modeling by Estimating Gradients of the Data Distribution,NCSNv2fromImproved Techniques for Training Score-Based Generative Models, andDDPMfromDenoising Diffusion Probabilistic Models....