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Jul, 2023
通过学习扩散方式改进采样
Improved sampling via learned diffusions
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Lorenz Richter, Julius Berner, Guan-Horng Liu
TL;DR
该论文提出了基于深度学习的方法来对非归一化目标密度进行建模,并使用特定问题的Schrödinger桥问题来确定在给定先验分布和指定目标之间的最有可能的随机演变,其中包括前面出现的目标作为特殊情况。
Abstract
Recently, a series of papers proposed
deep learning
-based approaches to sample from unnormalized target densities using
controlled diffusion processes
. In this work, we identify these approaches as special cases
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