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#	Item
131	Man-Made Structure Detection in Natural Images using a Causal Multiscale Random Field Sanjiv Kumar and Martial Hebert The Robotics Institute, Carnegie Mellon University Pittsburgh, PA 15213, USA, {skumar, hebert}@ri.cmu. Add to Reading List Source URL: www.sanjivk.com Language: English - Date: 2010-06-01 18:50:22 Statistics Vision Segmentation Edge detection Feature Thresholding Pattern recognition Histogram Image processing Computer vision Imaging
132	Microsoft Word - dlp-hs-fpga-ds-v14.doc Add to Reading List Source URL: www.ftdichip.com Language: English - Date: 2012-05-14 07:24:52 Computing Electronics Field-programmable gate array DDR2 SDRAM Synchronous dynamic random-access memory Joint Test Action Group Dynamic random-access memory EEPROM Universal Serial Bus Computer hardware Computer memory SDRAM
133	Herding Dynamic Weights for Partially Observed Random Field Models Max Welling Bren School of Information and Computer Science University of California, Irvine Irvine, USA Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2009-05-27 23:11:24
134	arXiv:1301.4168v2 [cs.LG] 16 MarHerded Gibbs Sampling Luke Bornn Harvard University Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-04-19 06:38:10 Applied mathematics Statistical mechanics Markov chain Monte Carlo Gibbs sampling Monte Carlo methods Conditional random field Gibbs algorithm Markov chain Viterbi algorithm Statistics Probability and statistics Markov models
135	Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study Sanjiv Kumar, Jonas August, and Martial Hebert The Robotics Institute, Carnegie Mellon University Pittsburgh, PA 15213 Add to Reading List Source URL: www.sanjivk.com Language: English - Date: 2010-06-01 18:50:53 Graphical models Bayesian statistics Probability theory Maximum likelihood Likelihood function Conditional random field Belief propagation Statistics Estimation theory M-estimators
136	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
137	The Effect of a Random Wave Field on Wave Induced Pore Pressure Generation Add to Reading List Source URL: www.flow-offshore.nl Language: English - Date: 2015-04-16 04:12:21
138	Introduction—Koalas, Trees and Strange Boundaries Working with a Continuous Random Field Marks! Conclusion Complex point processes without grids or pain Janine Illian, Daniel Simpson, Finn Lindgren, Håvard Rue, Sigru Add to Reading List Source URL: www.math.ntnu.no Language: English - Date: 2011-02-05 04:04:03
139	The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects John Winn Microsoft Research Cambridge Cambridge, UK Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2006-04-03 06:06:23
140	Exploiting structure when sampling from a Gaussian Markov random field Three unusual methods for GMRF calculations Daniel Simpson with Ian Turner and Tony Pettitt Institutt for matematiske fag 24 February, 2010 Add to Reading List Source URL: www.math.ntnu.no Language: English - Date: 2010-03-03 15:18:02

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