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Approximate inference in high-dimensional, discrete probabilistic models is a central problem in computational statistics and machine learning.
The detection of patterns in Alyawara nonverbal behavior
Woodrow W Denham · 1973
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Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
Charles E Antoniak · 1974
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Exchangeability and related topics
David Aldous · 1985
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On the statistical analysis of dirty pictures
Julian Besag · 1986
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Nonuniversal critical dynamics in Monte Carlo simulations
Robert H Swendsen and Jian-Sheng Wang · 1987
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The adaptive nature of human categorization
John R Anderson · 1991
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Default probability
Daniel N Osherson, Joshua Stern, Ormond Wilkie, Michael Stob, and Edward E Smith · 1991
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Bayesian density estimation and inference using mixtures
Michael D Escobar and Mike West · 1995
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Improving the mean field approximation via the use of mixture distributions
Tommi S Jaakkola and Michael I Jordan · 1998
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Loopy belief propagation for approximate inference: An empirical study
Kevin P Murphy, Yair Weiss, and Michael I Jordan · 1999
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Variational inference in probabilistic models
Neil D Lawrence · 2000
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Sequential Monte Carlo methods in practice
Arnaud Doucet, Nando De Freitas, Neil Gordon, et al · 2001
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The infinite hidden Markov model
Matthew J Beal, Zoubin Ghahramani, and Carl E Rasmussen · 2002
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Finding the M most probable configurations in arbitrary graphical models
Chen Yanover and Yair Weiss · 2003
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Particle filters for mixture models with an unknown number of components
Paul Fearnhead · 2004
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Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering
R Quian Quiroga, Z Nadasdy, and Y Ben-Shaul · 2004
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V-measure: A conditional entropy-based external cluster evaluation measure
Andrew Rosenberg and Julia Hirschberg · 2007
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Truncated importance sampling
Edward L Ionides · 2008
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Beam sampling for the infinite hidden Markov model
Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, and Zoubin Ghahramani · 2008
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Graphical models, exponential families, and variational inference
Martin J Wainwright and Michael I Jordan · 2008
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A nonparametric Bayesian alternative to spike sorting
Frank Wood and Michael J Black · 2008
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Particle-based variational inference for continuous systems
Andrew Frank, Padhraic Smyth, and Alexander T Ihler · 2009
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Monte Carlo Statistical Methods
Christian P Robert and George Casella · 2004
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Learning systems of concepts with an infinite relational model
Charles Kemp, Joshua B Tenenbaum, Thomas L Griffiths, Takeshi Yamada, and Naonori Ueda · 2006
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Hierarchical Dirichlet processes
Yee Whye Teh, Michael I Jordan, Matthew J Beal, and David M Blei · 2006
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Fast search for Dirichlet process mixture models
Hal Daume · 2007
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Fast Bayesian inference in Dirichlet process mixture models
Lianming Wang and David B Dunson · 2011
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Bucket and mini-bucket schemes for m best solutions over graphical models
Natalia Flerova, Emma Rollon, and Rina Dechter · 2012
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Nonparametric variational inference
Samuel Gershman, Matt Hoffman, and David Blei · 2012
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