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Graphical models
Results: 1083

#	Item
921	Overview Graphical models and Bayesian data analysis Computing like a Bayesian BUGS and features Conclusion Add to Reading List Source URL: www.stat.columbia.edu Language: English - Date: 2004-08-08 13:47:20 Andrew Gelman Just another Gibbs sampler Statistics Bayesian statistics Graphical model
922	TUESDAY’S LESSON Making Molecular Models Your Own The Concord Consortium’s Library of Models includes over one hundred models and activities to enhance students’ understanding of molecular interactions. Created in Add to Reading List Source URL: mw.concord.org Language: English - Date: 2014-03-07 07:40:02 Graphical user interfaces AmigaOS Workbench Text box Insert key Mouse Computer keyboard GUI widget System software Software Humanâ€“computer interaction
923	Unsupervised Evidence Integration Philip M. Long Vinay Varadan Sarah Gilman Mark Treshock Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:14:16 Statistical dependence Graphical models Expectation–maximization algorithm Missing data Conditional independence Variance Independence Algorithm Maximum likelihood Statistics Probability theory Estimation theory
924	ESS 575, Systems Ecology: An Introduction to Ecological Modeling Tom Hobbs, B227 NESB, [removed]o), [removed]mobile), Email: [removed] January 18, 2013 Lecture in NESB A302, Tues. and Thurs., 9:30-10 Add to Reading List Source URL: warnercnr.colostate.edu Language: English - Date: 2013-08-28 13:29:12 Statistical inference Graphical models Bayesian inference Just another Gibbs sampler Hierarchical Bayes model Bayesian linear regression Markov chain Monte Carlo Maximum likelihood Estimation theory Statistics Bayesian statistics Statistical theory
925	Expanded graphical models: Inference, Model comparison, Model checking, Fake-data debugging, and Model understanding Andrew Gelman Dept of Statistics and Dept of Political Science, Columbia University, New York Add to Reading List Source URL: www.stat.columbia.edu Language: English - Date: 2011-07-29 11:37:52 Statistical models Andrew Gelman Economic model Scientific modelling Graphical model Conceptual model Gelman Modeling language Statistics Ethology Philosophy of mind
926	THIS IS A DRAFT VERSION. FINAL VERSION TO BE PUBLISHED AT NIPS ’06 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation Yee Whye Teh Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2008-10-31 18:54:20 Statistical models Graphical models Variational Bayesian methods Latent Dirichlet allocation Gibbs sampling Bayesian network Normal distribution Marginal likelihood Mixture model Statistics Bayesian statistics Probability and statistics
927	Efficient Structured Prediction with Latent Variables for General Graphical Models Alexander G. Schwing Computer Science Department, ETH Zurich, 8092 Zurich, Switzerland Tamir Hazan Toyota Technological Institute at Chic Add to Reading List Source URL: icml.cc Language: English - Date: 2012-06-07 13:20:18 Structured SVM Function Constructible universe Variance Vector space Lambda calculus Algebra Mathematics Probability theory
928	A General Framework for Mixed Graphical Models Genevera I. Allen Dobelman Family Junior Chair, Department of Statistics and Electrical and Computer Engineering, Rice University, Department of Pediatrics-Neurology, Baylor Add to Reading List Source URL: srcos2014.blogs.rice.edu Language: English - Date: 2014-07-31 13:06:15 Graphical models Bayesian statistics Networks Probability theory Markov random field Exponential family Generalized linear model Sufficient statistic Graphical models for protein structure Statistics Statistical models Probability and statistics
929	GENERAL FRAMEWORK FOR MIXED GRAPHICAL MODELS Yulia Baker Departments of Statistics and Electrical & Computer Engineering, Rice University, Department of Pediatrics-Neurology, Baylor College of Medicine, & Jan and Dan Dun Add to Reading List Source URL: srcos2014.blogs.rice.edu Language: English - Date: 2014-07-30 17:09:37 Statistics Theoretical computer science Statistical models Bayesian statistics Conditional random field Markov random field Mutation P53 Gene regulatory network Biology Graphical models Networks
930	Learning Transcriptional Regulatory Relationships Using Sparse Graphical Models Xiang Zhang1,2,3., Wei Cheng3., Jennifer Listgarten1, Carl Kadie1, Shunping Huang3, Wei Wang3, David Heckerman1* 1 Microsoft Research, Los A Add to Reading List Source URL: www.cs.ucla.edu Language: English - Date: 2012-09-12 21:42:32 Genetics Microarrays Systems biology Gene regulatory network Gene DNA microarray Promoter Bioinformatics Human genome Biology Gene expression Molecular biology

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