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Markov model
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#	Item
11	A NON-UNIFORMLY SAMPLED MARKOV RANDOM FIELD MODEL FOR MAP RECONSTRUCTION OF MAGNETOENCEPHALOGRAM IMAGES * Alan H. Gardinert and Brian D. Jeffst t Lockheed Martin Federal Systems $ Department of Electrical and Computer En Add to Reading List Source URL: www.et.byu.edu - Date: 2009-10-14 12:22:26
12	A GENERALIZED GAUSS MARKOV MODEL FOR SPACE OBJECTS IN BLIND RESTORATION OF ADAPTIVE OPTICS TELESCOPE IMAGES * Brian D. Jeffst, Sheila Hongt and Julian Christout Computer Engineering, 459 CB, Brigham Young University, Pro Add to Reading List Source URL: www.et.byu.edu - Date: 2009-10-14 12:22:25
13	Appears in Proceedings of the Annual Meeting of the Cognitive Science Society, 2015 (CogSciHidden Markov model analysis reveals better eye movement strategies in face recognition Tim Chuk ( Add to Reading List Source URL: visal.cs.cityu.edu.hk - Date: 2016-01-02 01:32:19
14	Probabilistic Model Checking Part 1: Discrete-Time Markov Chains Joost-Pieter Katoen RWTH Aachen University Software Modeling and Verification Group Course on Probabilistic Model Checking, IMT Lucca, Italy, 2014 Add to Reading List Source URL: dl.dropboxusercontent.com
15	iSWoM: The incremental Storage Workload Model based on Hidden Markov Models Tiberiu Chis and Peter G. Harrison Department of Computing, Imperial College London, Huxley Building, 180 Queens Gate, London SW7 2RH, UK {tc207 Add to Reading List Source URL: pubs.doc.ic.ac.uk - Date: 2013-09-26 05:04:14
16	Sparse pairwise Markov model learning for anomaly detection in heterogeneous data Romain Laby, Alexandre Gramfort, Fran¸cois Roueff, Cyrille Enderli, Larroque Alain To cite this version: Add to Reading List Source URL: hal-institut-mines-telecom.archives-ouvertes.fr - Date: 2016-12-19 12:56:27
17	Continuous-Time Markov Chains Overview Probabilistic Model Checking Part 2: Continuous-Time Markov Chains Add to Reading List Source URL: dl.dropboxusercontent.com
18	Interactive Exploration of Developer Interaction Traces using a Hidden Markov Model Kostadin Damevski Hui Chen Add to Reading List Source URL: damevski.github.io - Date: 2016-08-26 16:33:27
19	Statistical Model Checking for Markov Decision Processes David Henriques∗† , Jo˜ao G. Martins∗‡ , Paolo Zuliani∗ , Andr´e Platzer∗ , Edmund M. Clarke∗ ∗ Computer † SQIG Add to Reading List Source URL: symbolaris.com - Date: 2014-08-04 10:11:57
20	In this talk, I will introduce hinge-loss Markov random fields (HLMRFs), a new kind of probabilistic graphical model that supports scalable collective inference from richly structured data. HL-MRFs unify three different Add to Reading List Source URL: mmds-data.org - Date: 2016-06-23 15:50:48

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