分层变分模型与辅助深生成模型等价性的注记
Note on the equivalence of hierarchical variational models and auxiliary deep generative models
摘要：
本文比较了两个最近发表的机器学习方法，用于构建灵活，但易于处理的变分隐变量后验族。第一种方法，称为“分层变分模型”，丰富的推理模型与额外的变量，而另一种，称为“辅助深度生成模型”，丰富的生成模型。我们的结论是，这两种方法在数学上是等价的。
英文摘要：
This note compares two recently published machine learning methods for constructing flexible, but tractable families of variational hidden-variable posteriors. The first method, called "hierarchical variational models" enriches the inference model with an extra variable, while the other, called "auxiliary deep generative models", enriches the generative model instead. We conclude that the two methods are mathematically equivalent.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
