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Feb, 2012
潜变量因果模型中计算干预分布的高效算法
An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models
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Ilya Shpitser, Thomas S. Richardson, James M. Robins
TL;DR
本文介绍了一种可以计算由混合图表示的潜在变量因果模型的干预分布的算法，这个算法可以被看作是变量消除在混合图情况下的推广，并且在混合图的广义树宽度方面呈指数级别增长。
Abstract
probabilistic inference
in
graphical models
is the task of computing marginal and conditional densities of interest from a factorized representation of a joint probability distribution. Inference algorithms such
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