Inference Suboptimality in Variational Autoencoders by Chris Cremer and others (2018)

proceedings.mlr.press/v80/cremer18a.html

Primary PDF: proceedings.mlr.press/v80/cremer18a/cremer18a.pdf . Title-page byline: Chris Cremer, Xuechen Li and David Duvenaud; PMLR80,1078–1086(2018). Table1 on printed page1079 defines the inference, approximation and amortization gaps; the introduction specifies the optimal per-observation approximation within the chosen family.

§3.1 equation8, approximation/amortization decomposition; §3.2 and Figure2, expressive approximations; §3.4, separate optimization per observation and 100 Monte Carlo samples per bound estimate

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