Markov networks

Results: 388



#Item
21Social Networks–96  The accuracy of small world chains in social networks Peter D. Killworth a,∗ , Christopher McCarty b , H. Russell Bernard c , Mark House b

Social Networks–96 The accuracy of small world chains in social networks Peter D. Killworth a,∗ , Christopher McCarty b , H. Russell Bernard c , Mark House b

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Source URL: nersp.nerdc.ufl.edu

Language: English - Date: 2007-06-20 07:27:56
22Minimum trajectory error training for deep neural networks, combined with stacked bottleneck features Zhizheng Wu Simon King

Minimum trajectory error training for deep neural networks, combined with stacked bottleneck features Zhizheng Wu Simon King

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Source URL: www.cstr.inf.ed.ac.uk

Language: English
23A Short Introduction to Probabilistic Soft Logic  Angelika Kimmig1,2 , Stephen H. Bach1 , Matthias Broecheler3 , Bert Huang1 , Lise Getoor1 1 University of Maryland, 2 KU Leuven, 3 Aurelius LLC

A Short Introduction to Probabilistic Soft Logic Angelika Kimmig1,2 , Stephen H. Bach1 , Matthias Broecheler3 , Bert Huang1 , Lise Getoor1 1 University of Maryland, 2 KU Leuven, 3 Aurelius LLC

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Source URL: psl.umiacs.umd.edu

Language: English - Date: 2013-06-14 19:26:51
24Collective 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

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

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Source URL: stephenbach.net

Language: English - Date: 2013-06-10 18:15:10
25Journal of Artificial Intelligence Research–1178  Submitted 12/15; publishedExploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks

Journal of Artificial Intelligence Research–1178 Submitted 12/15; publishedExploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks

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Source URL: jair.org

Language: English - Date: 2016-04-28 15:06:13
26Probabilistic Soft Logic for Semantic Textual Similarity Islam Beltagy§ Katrin Erk† Raymond Mooney§ § Department of Computer Science

Probabilistic Soft Logic for Semantic Textual Similarity Islam Beltagy§ Katrin Erk† Raymond Mooney§ § Department of Computer Science

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Source URL: www.cs.utexas.edu

Language: English - Date: 2014-07-01 12:33:24
27Sampling for Approximate Inference in Continuous Time Bayesian Networks Yu Fan Christian R. Shelton

Sampling for Approximate Inference in Continuous Time Bayesian Networks Yu Fan Christian R. Shelton

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Source URL: rlair.cs.ucr.edu

Language: English - Date: 2011-01-19 19:25:42
28CONTINUOUS TIME BAYESIAN NETWORKS  A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY

CONTINUOUS TIME BAYESIAN NETWORKS A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY

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Source URL: robotics.stanford.edu

Language: English - Date: 2008-05-19 23:42:02
29Language Understanding for Text-based Games using Deep Reinforcement Learning Karthik Narasimhan∗ CSAIL, MIT

Language Understanding for Text-based Games using Deep Reinforcement Learning Karthik Narasimhan∗ CSAIL, MIT

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Source URL: arxiv.org

Language: English - Date: 2015-09-14 21:25:04
30Social Networks–96  The accuracy of small world chains in social networks Peter D. Killworth a,∗ , Christopher McCarty b , H. Russell Bernard c , Mark House b

Social Networks–96 The accuracy of small world chains in social networks Peter D. Killworth a,∗ , Christopher McCarty b , H. Russell Bernard c , Mark House b

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Source URL: nersp.nerdc.ufl.edu

Language: English - Date: 2007-02-01 12:43:34