Inference compilation and universal probabilistic programming

Inference compilation and universal probabilistic programming

We introduce a method for using deep neural networks to amortize the cost of inference in models from the family induced by universal probabilistic programming languages, establishing a framework that combines the strengths of probabilistic programming and deep learning methods. We call what we do “...

書誌詳細
主要な著者:	Le, T, Baydin, A, Wood, F
フォーマット:	Conference item
出版事項:	Journal of Machine Learning Research 2017

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