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I presented the importance-weighted hierarchical variational inference (IWHVI) paper: https://arxiv.org/abs/1905.03290. IWHVI is a new family of tighter variational upper bounds on marginal log density that generalizes the hierarchical variational model (HVM) upper bound and semi-implicit variational inference bound (SIVI). It enjoys the same nice guarantees as the importance-weighted autoencoder (IWAE) bound and lends itself to similar jackknife debiasing estimators.
I presented the importance-weighted hierarchical variational inference (IWHVI) paper: https://arxiv.org/abs/1905.03290. IWHVI is a new family of tighter variational upper bounds on marginal log density that generalizes the hierarchical variational model (HVM) upper bound and semi-implicit variational inference bound (SIVI). It enjoys the same nice guarantees as the importance-weighted autoencoder (IWAE) bound and lends itself to similar jackknife debiasing estimators.
My slides
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