Amortized Monte Carlo integration

Amortized Monte Carlo integration

Current approaches to amortizing Bayesian inference focus solely on approximating the posterior distribution. Typically, this approximation is, in turn, used to calculate expectations for one or more target functions{—}a computational pipeline which is inefficient when the target function(s) are kno...

書誌詳細
主要な著者:	Goliński, A, Wood, F, Rainforth, T
フォーマット:	Conference item
出版事項:	Proceedings of Machine Learning Research 2019

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