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 “...
Main Authors: | Le, T, Baydin, A, Wood, F |
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Format: | Conference item |
Izdano: |
Journal of Machine Learning Research
2017
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