Joint Stochastic Approximation learning of Helmholtz Machines

20 Mar 2016Haotian XuZhijian Ou

Though with progress, model learning and performing posterior inference still remains a common challenge for using deep generative models, especially for handling discrete hidden variables. This paper is mainly concerned with algorithms for learning Helmholz machines, which is characterized by pairing the generative model with an auxiliary inference model... (read more)

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