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Variational inference is a scalable technique for approximate Bayesian inference.
An introduction to variational methods for graphical models
Michael I Jordan, Zoubin Ghahramani, Tommi S Jaakkola, and Lawrence K Saul · 1999
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Christian P Robert and George Casella · 1999
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GaP: a factor model for discrete data
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Variational message passing
John M Winn and Christopher M Bishop · 2005
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Pattern Recognition and Machine Learning
Christopher M Bishop · 2006
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Andrew Gelman and Jennifer Hill · 2006
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Graphical models, exponential families, and variational inference
Martin J Wainwright and Michael I Jordan · 2008
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Church: A language for generative models
Noah D Goodman, Vikash K Mansinghka, Daniel Roy, Keith Bonawitz, and Joshua B Tenenbaum · 2008
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The variational Gaussian approximation revisited
Manfred Opper and Cédric Archambeau · 2009
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Bayesian inference for nonnegative matrix factorisation models
Ali Taylan Cemgil · 2009
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Adaptive subgradient methods for online learning and stochastic optimization
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Matthew D Hoffman, David M Blei, Chong Wang, and John Paisley · 2013
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Stochastic backpropagation and approximate inference in deep generative models
Danilo J Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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Black box variational inference
Rajesh Ranganath, Sean Gerrish, and David Blei · 2014
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On using control variates with stochastic approximation for variational Bayes
Tim Salimans and David Knowles · 2014
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Doubly stochastic variational Bayes for non-conjugate inference
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Venture: a higher-order probabilistic programming platform with programmable inference
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Automated variational inference in probabilistic programming
David Wingate and Theophane Weber · 2013
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Overview of the ImageCLEF 2013 Scalable Concept Image Annotation Subtask
Mauricio Villegas, Roberto Paredes, and Bart Thomee · 2013
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Variational Bayesian inference for linear and logistic regression
Jan Drugowitsch · 2013
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Vikash Mansinghka, Daniel Selsam, and Yura Perov · 2014
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A new approach to probabilistic programming inference
Frank Wood, Jan Willem van de Meent, and Vikash Mansinghka · 2014
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Statistical Theory and Inference
David J Olive · 2014
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Adam: A method for stochastic optimization
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Stan Modeling Language Users Guide and Reference Manual , 2015
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