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Parameterizing the approximate posterior of a generative model with neural networks has become a common theme in recent machine learning research.
Information theoretical analysis of multivariate correlation
Satosi Watanabe · 1960
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Learning factorial codes by predictability minimization
Jürgen Schmidhuber · 1992
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From few to many: Illumination cone models for face recognition under variable lighting and pose
David J. Kriegman Athinodoros S. Georghiades, Peter N. Belhumeur · 2001
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Measuring statistical dependence with Hilbert-Schmidt norms
Arthur Gretton, Olivier Bousquet, Alex Smola, and Bernhard Schölkopf · 2005
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Acquiring linear subspaces for face recognition under variable lighting
David J Kriegman Kuang-Chih Lee, Jeffrey Ho · 2005
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Data analysis using regression and multilevel/hierarchical models
Andrew Gelman and Jennifer Hill · 2007
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Kernel measures of conditional dependence
Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, and Bernhard Schölkopf · 2008
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A kernel statistical test of independence
Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, and Alexander J. Smola · 2008
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Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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Supervised dictionary learning
Julien Mairal, Jean Ponce, Guillermo Sapiro, Andrew Zisserman, and Francis R. Bach · 2009
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Efficient learning of deep boltzmann machines
Ruslan Salakhutdinov and Hugo Larochelle · 2010
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Systems biology of vaccination for seasonal influenza in humans
Helder I Nakaya, Jens Wrammert, Eva K Lee, Luigi Racioppi, Stephanie Marie-Kunze, W Nicholas Haining, Anthony R Means, Sudhir P Kasturi, Nooruddin Khan, Gui Mei Li, Megan McCausland, Vibhu Kanchan, Kenneth E Kokko, Shuzhao Li, Rivka Elbein, Aneesh K Mehta, Alan Aderem, Kanta Subbarao, Rafi Ahmed, and Bali Pulendran · 2011
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Measuring reproducibility of high-throughput experiments
Qunhua Li, James B Brown, Haiyan Huang, and Peter J Bickel · 2011
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Lower and Upper bounds for approximation of the Kullback-Leibler divergence between Gaussian mixture models
Jean-Louis Durrieu, Jean-Philippe Thiran, and Finnian Kelly · 2012
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A Kernel Two-Sample Test
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
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Auto-Encoding Variational Bayes
Diederik P Kingma and Max Welling · 2014
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Semi-supervised learning with deep generative models
Diederik P Kingma, Shakir Mohamed, Danilo Jimenez Rezende, and Max Welling · 2014
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Validation of noise models for single-cell transcriptomics
Dominic Grun, Lennart Kester, and Alexander van Oudenaarden · 2014
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Moderated estimation of fold change and dispersion for rna-seq data with deseq2
Michael I. Love, Wolfgang Huber, and Simon Anders · 2014
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Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Allon M Klein, Linas Mazutis, Ilke Akartuna, Naren Tallapragada, Adrian Veres, Victor Li, Leonid Peshkin, David A Weitz, and Marc W Kirschner · 2015
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Mast: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell rna sequencing data
Greg Finak, Andrew McDavid, Masanao Yajima, Jingyuan Deng, Vivian Gersuk, Alex K Shalek, Chloe K Slichter, Hannah W Miller, M Juliana McElrath, Martin Prlic, et al · 2015
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β \beta -VAE: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
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Kernel-based tests for joint independence
Pfister Niklas, Bühlmann Peter, Schölkopf Bernhard, and Peters Jonas · 2017
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Disentangling by Factorising
Hyunjik Kim and Andriy Mnih · 2017
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Understanding disentangling in
Christopher P Burgess, Irina Higgins, Arka Pal, Loic Matthey, Nick Watters, Guillaume Desjardins, and Alexander Lerchner · 2017
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Scaling single-cell genomics from phenomenology to mechanism
Amos Tanay and Aviv Regev · 2017
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Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq
Michael B Cole, Davide Risso, Allon Wagner, David DeTomaso, John Ngai, Elizabeth Purdom, Sandrine Dudoit, and Nir Yosef · 2017
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Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells
Florian Buettner, Kedar N Natarajan, F Paolo Casale, Valentina Proserpio, Antonio Scialdone, Fabian J Theis, Sarah A Teichmann, John C Marioni, and Oliver Stegle · 2015
Cited alongside, same era.
The Variational Fair Autoencoder
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, and Richard Zemel · 2016
Cited alongside, same era.
Composing graphical models with neural networks for structured representations and fast inference
Matthew Johnson, David K Duvenaud, Alex Wiltschko, Ryan P Adams, and Sandeep R Datta · 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
Cited alongside, same era.
Adversarial Autoencoders
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey · 2016
Cited alongside, same era.
ELBO surgery: yet another way to carve up the variational evidence lower bound
Matthew D Hoffman and Matthew J Johnson · 2016
Cited alongside, same era.
Importance weighted autoencoders
Yuri Burda, Roger B. Grosse, and Ruslan Salakhutdinov · 2016
Cited alongside, same era.
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Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning
Bo Wang, Junjie Zhu, Emma Pierson, Daniele Ramazzotti, and Serafim Batzoglou · 2017
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Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets
Evan Macosko, Anindita Basu, Rahul Satija, James Nemesh, Karthik Shekhar, Melissa Goldman, Itay Tirosh, Allison Bialas, Nolan Kamitaki, Emily Martersteck, John Trombetta, David Weitz, Joshua Sanes, Alex Shalek, Aviv Regev, and Steven McCarroll · 2017
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An adaptive test of independence with analytic kernel embeddings
Wittawat Jitkrittum, Zoltán Szabó, and Arthur Gretton · 2017
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Isolating sources of disentanglement in variational autoencoders
Tian Qi Chen, Xuechen Li, Roger Grosse, and David Duvenaud · 2018
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Characteristic and universal tensor product kernels
Zoltán Szabó and Bharath K. Sriperumbudur · 2018
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Learning to Explain: An Information-Theoretic Perspective on Model Interpretation
Jianbo Chen, Le Song, Martin J Wainwright, and Michael I Jordan · 2018
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Bayesian Inference for a Generative Model of Transcriptome Profiles from Single-cell RNA Sequencing
Romain Lopez, Jeffrey Regier, Michael B. Cole, Michael I. Jordan, and Nir Yosef · 2018
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A general and flexible method for signal extraction from single-cell rna-seq data
Davide Risso, Fanny Perraudeau, Svetlana Gribkova, Sandrine Dudoit, and Jean-Philippe Vert · 2018
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Sensitivity maps of the Hilbert–Schmidt independence criterion
Adrián Pérez-Suay and Gustau Camps-Valls · 2018
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