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Graphical models
Results: 1083

#	Item
51	Low Level Vision via Switchable Markov Random Fields Dahua Lin CSAIL, MIT John Fisher CSAIL, MIT Add to Reading List Source URL: dahua.me Language: English - Date: 2013-01-06 22:24:23 Statistics Artificial intelligence Computer vision Graphical models Machine learning Image processing Image segmentation Bayesian statistics Markov random field Conference on Computer Vision and Pattern Recognition Mixture model Noise reduction
52	Learning Latent Groups with Hinge-loss Markov Random Fields Stephen H. Bach Bert Huang Lise Getoor University of Maryland, College Park, Maryland 20742, USA Add to Reading List Source URL: stephenbach.net Language: English - Date: 2013-06-14 15:37:03 Statistics Probability theory Graphical models Machine learning Statistical models Statistical theory Bayesian statistics Markov random field Latent variable Expectationmaximization algorithm Marginal likelihood Conditional random field
53	ECI Telecom Employs I-Logix’ Rhapsody and UML Graphical Coding Techniques To Develop Embedded Digital Cross Connect Applications In the telecommunications world, those developing applications in software have much to c Add to Reading List Source URL: www.uml.org Language: English - Date: 2016-03-23 09:20:58 Software engineering Computing Software Project management Infographics Diagrams Unified Modeling Language I-Logix Models of computation Software development State diagram Rhapsody
54	1 Brain Anatomical Structure Segmentation by Hybrid Discriminative/Generative Models Zhuowen Tu, Katherine L. Narr, Piotr Doll´ar, Ivo Dinov, Paul M. Thompson, and Arthur W. Toga Add to Reading List Source URL: pages.ucsd.edu Language: English - Date: 2007-08-09 13:56:19 Artificial intelligence Machine learning Learning Graphical models Image segmentation Discriminative model Principal component analysis Conditional random field AdaBoost Functional magnetic resonance imaging Markov random field Bag-of-words model in computer vision
55	Automated co-evolution of GMF editor models Davide Di Ruscio1 , Ralf L¨ammel2 , Alfonso Pierantonio1 1 2 Add to Reading List Source URL: www.mancoosi.org Language: English - Date: 2012-12-16 04:54:55 Software Computing Eclipse Graphical Modeling Framework Eclipse Modeling Framework Model-driven engineering Graphical Editing Framework GMF Metamodeling Object Process Methodology Conceptual model Entityrelationship model
56	Collective Activity Detection using Hinge-loss Markov Random Fields Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry Davis University of Maryland College Park, MD 20742 {blondon,sameh,bach,bert,g Add to Reading List Source URL: stephenbach.net Language: English - Date: 2013-06-10 18:15:10 Artificial intelligence Probability Statistics Bayesian statistics Markov networks Graphical models Markov random field Probability theory Image segmentation Probabilistic soft logic Activity recognition Support vector machine
57	Journal of Artificial Intelligence Research–1178 Submitted 12/15; publishedExploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks Add to Reading List Source URL: jair.org Language: English - Date: 2016-04-28 15:06:13 Statistics Graphical models Probability Estimation theory Robot control Dynamic Bayesian network Probability theory Bayesian network Causality Particle filter Partially observable Markov decision process Belief propagation
58	PITCH SPELLING WITH CONDITIONALLY INDEPENDENT VOICES Gabi Teodoru School of Informatics Indiana University ABSTRACT Add to Reading List Source URL: music.informatics.indiana.edu Language: English - Date: 2008-02-18 09:48:52 Statistics Markov models Statistical models Mathematics Applied mathematics Markov chain Expectationmaximization algorithm Bayesian network Graphical model BaumWelch algorithm Algorithm Dynamic programming
59	Microsoft Word - ICMR-06 Months-Report From IF Add to Reading List Source URL: www.icmr.nic.in Language: English - Date: 2014-09-19 07:33:29 Statistics Science Logic Statistical theory Philosophy of science Statistical inference Inductive reasoning Graphical models Causal inference Agent-based model Bayesian inference Causality
60	Latent Trees for Estimating Intensity of Facial Action Units Sebastian Kaltwang Imperial College London Sinisa Todorovic Oregon State University Add to Reading List Source URL: ibug.doc.ic.ac.uk Language: English - Date: 2015-11-12 06:27:16 Machine learning Statistics Learning Graphical models Conditional random field Support vector machine Expectationmaximization algorithm

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