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Marginal likelihood
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#	Item
11	FAST BAYESIAN COMPRESSIVE SENSING USING LAPLACE PRIORS S. Derin Babacan1 , Rafael Molina2 , Aggelos K. Katsaggelos1 1 2 Department of Electrical Engineering Add to Reading List Source URL: decsai.ugr.es Language: English - Date: 2009-03-24 12:49:57 Statistics Probability Mathematical analysis Probability distributions Linear algebra Bayesian statistics Laplace distribution Compressed sensing Marginal likelihood Relevance vector machine Bayesian network Bayesian inference
12	Downloaded from http://rsta.royalsocietypublishing.org/ on December 28, 2015 rsta.royalsocietypublishing.org A hierarchical Bayesian framework for force field Add to Reading List Source URL: www.cse-lab.ethz.ch Language: English - Date: 2015-12-28 04:01:00 Statistics Statistical theory Statistical models Estimation theory Bayesian network Networks Bayesian inference Linear regression Marginal likelihood
13	Exploiting Task-Based Parallelism in Bayesian Uncertainty Quantification Panagiotis E. Hadjidoukas1(B) , Panagiotis Angelikopoulos1 , Lina Kulakova1 , Costas Papadimitriou2 , and Petros Koumoutsakos1 1 Add to Reading List Source URL: www.cse-lab.ethz.ch Language: English - Date: 2015-08-03 10:21:45 Statistics Statistical theory Bayesian statistics Estimation theory Parallel computing Bayesian network Bayesian inference Loss function Likelihood function Uncertainty quantification Markov chain Monte Carlo Marginal likelihood
14	Bayesian K-Means as a “Maximization-Expectation” Algorithm October 18, 2007 Abstract Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2007-10-18 14:00:50 Statistical theory Expectation–maximization algorithm Missing data Statistical models Maximum likelihood Fisher information Variational Bayesian methods Marginal likelihood Mixture model Statistics Estimation theory Bayesian statistics
15	Model Selection in Compositional Spaces by Roger Baker Grosse B.S., Stanford UniversityM.S., Stanford University (2008) Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2015-06-03 15:15:50 Bayesian statistics Statistical models Generative model Bayes factor Variational Bayesian methods Variational message passing Marginal likelihood Supervised learning Gibbs sampling Statistics Machine learning Probability and statistics
16	arXiv:1312.6114v9 [stat.ML] 10 AprAuto-Encoding Variational Bayes Max Welling Machine Learning Group Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2014-04-19 07:05:02 Statistical models Statistical inference Expectation–maximization algorithm Missing data Variational Bayesian methods Maximum likelihood Normal distribution Bayesian network Marginal likelihood Statistics Estimation theory Bayesian statistics
17	arXiv:1401.2838v1 [cs.LG] 13 JanGPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation Max Welling Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2014-04-19 07:04:55 Statistical inference Econometrics Confidence interval Measurement Marginal likelihood Likelihood function Normal distribution Markov chain Maximum likelihood Statistics Estimation theory Bayesian statistics
18	THIS IS A DRAFT VERSION. FINAL VERSION TO BE PUBLISHED AT NIPS ’06 Structure Learning in Markov Random Fields Sridevi Parise Bren School of Information and Computer Science Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2006-09-04 17:32:02 Probability theory Estimation theory Graphical models Marginal likelihood Expectation–maximization algorithm Variational Bayesian methods Normal distribution Maximum likelihood Bayesian network Statistics Bayesian statistics Statistical theory
19	Evidence Estimation for Bayesian Partially Observed MRFs Yutian Chen Department of Computer Science University of California, Irvine Irvine, CA 92697 Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-02-14 03:02:58 Normal distribution Expectation–maximization algorithm Variational Bayesian methods Bayesian network Markov chain Monte Carlo Maximum likelihood Deviance information criterion Pierre-Simon Laplace Markov random field Statistics Bayesian statistics Marginal likelihood
20	Marginal set likelihood for semiparametric copula estimation Peter D. Hoff 1 Working Paper no. 65 Center for Statistics and the Social Sciences University of Washington Seattle, WA Add to Reading List Source URL: www.csss.washington.edu Language: English - Date: 2009-01-07 17:16:27 Multivariate statistics Regression analysis Copula Statistical dependence Multivariate normal distribution Normal distribution Conjugate prior Likelihood function Marginal likelihood Statistics Bayesian statistics Estimation theory

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