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• W2271421239 abstract "We introduce the variational R'enyi bound (VR) that extends traditional variational inference to R'enyi's alpha-divergences. This new family of variational lower-bounds unifies a number of existing variational methods, and enables a smooth interpolation from the evidence lower-bound to the log (marginal) likelihood that is controlled by the value of alpha. The reparameterization trick, Monte Carlo estimation and stochastic optimisation methods are deployed to obtain a unified implementation for the VR bound optimisation. We further consider negative alpha values and propose a novel variational inference method as a new special case in the proposed framework. Experiments on variational auto-encoders and Bayesian neural networks demonstrate the wide applicability of the VR bound." @default.
• W2271421239 created "2016-06-24" @default.
• W2271421239 creator A5038242041 @default.
• W2271421239 creator A5072490106 @default.
• W2271421239 date "2016-02-06" @default.
• W2271421239 modified "2023-09-27" @default.
• W2271421239 title "Variational Inference with Rényi Divergence." @default.
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• W2271421239 hasPublicationYear "2016" @default.
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