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Variational inference relies on flexible approximate posterior distributions.
Some iterative methods for improving orthonormality
Zdislav Kovarik · 1970
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An iterative algorithm for computing the best estimate of an orthogonal matrix
Åke Björck and Clazett Bowie · 1971
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A basis-kernel representation of orthogonal matrices
Xiaobai Sun and Christian Bischof · 1995
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On orthogonal block elimination
Christian Bischof and Xiaobai Sun · 1997
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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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Density estimation by dual ascent of the log-likelihood
Esteban G Tabak and Eric Vanden-Eijnden · 2010
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Stochastic variational inference
Matthew D. Hoffman, David M. Blei, Chong Wang, and John Paisley · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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A family of nonparametric density estimation algorithms
EG Tabak and Cristina V Turner · 2013
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NICE: non-linear independent components estimation
Laurent Dinh, David Krueger, and Yoshua Bengio · 2014
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Amortized inference in probabilistic reasoning
Samuel Gershman and Noah Goodman · 2014
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Efficient gradient-based inference through transformations between bayes nets and neural nets
Diederik Kingma and Max Welling · 2014
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Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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Generating Sentences from a Continuous Space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, and Samy Bengio · 2015
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Density estimation using Real NVP
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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David Ha, Andrew Dai, and Quoc V. Le · 2016
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Improved Variational Inference with Inverse Autoregressive Flow
Diederik P Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling · 2016
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Approximate inference for deep latent gaussian mixtures
Eric Nalisnick, Lars Hertel, and Padhraic Smyth · 2016
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Ladder Variational Autoencoders
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, and Ole Winther · 2016
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MADE: Masked Autoencoder for Distribution Estimation
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Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
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Markov Chain Monte Carlo and variational inference: Bridging the gap
Tim Salimans, Diederik Kingma, and Max Welling · 2015
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The variational Gaussian process
Dustin Tran, Rajesh Ranganath, and David M Blei · 2015
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Improving Variational Auto-encoders using Householder Flow
Jakub M Tomczak and Max Welling · 2016
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Conditional image generation with pixelcnn decoders
Aaron van den Oord, Nal Kalchbrenner, Lasse Espeholt, koray kavukcuoglu, Oriol Vinyals, and Alex Graves · 2016
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Variational inference with orthogonal normalizing flows
Leonard Hasenclever, Jakub Tomczak, Rianne van den Berg, and Max Welling · 2017
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Masked Autoregressive Flow for Density Estimation
George Papamakarios, Iain Murray, and Theo Pavlakou · 2017
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