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Stochastic variational inference tutorial

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    23 Nov 2014 Variational methods turn inference into optimization. ? With stochastic optimization: – Scale up with stochastic variational inference [Hoffman et
    Stochastic Variational. Inference. Reza Babanezhad rezababa@cs.ubc.ca. Page 2. Outline. • VI. • Monte Carlo Gradient Approximation. • Stochastic Variational
    We begin this review with a brief tutorial on variational inference, presenting the mathematical . Variational Inference amounts to applying stochastic.Let’s see how we go about doing variational inference in Pyro. .. and guide pairs leads to some complications (see the tutorial SVI Part III for a discussion).
    We learnt that the mean-field variational inference (VI) can be used to In the following we describe stochastic variational inference introduced by Hoffman et al.
    Shakir Mohamed. NIPS 2016 Tutorial · December 5, 2016 . Hoffman+, Stochastic Variational Inference, 2013. Part III: Stochastic gradients of the ELBO.
    Tutorial: Stochastic Variational Inference. David Madras. University of Toronto. March 16, 2017. David Madras (University of Toronto). SVI Tutorial. March 16
    3 Apr 2018 We start with a rather general view of the EM algorithm that also serves as a basis for discussing variational inference methods later.
    This tutorial (https://chrisdxie.files.wordpress.com/2016/06/in-depth-variational-inference-tutorial.pdf) answers most of your questions, and would probably be

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