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Dynamic Bayesian network
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#	Item
21	Spatio-Temporal Event Detection Using Dynamic Conditional Random Fields Add to Reading List Source URL: www.cse.ust.hk Language: English - Date: 2009-07-14 20:11:06 Data mining Wireless networking Wireless sensor network Bayesian network Conditional random field Causality Markov chain Anomaly detection Statistics Graphical models Networks
22	Inference in Hybrid Bayesian Networks using dynamic discretisation Martin Neil†‡ , Manesh Tailor‡ and David Marquez† † Department of Computer Science, Queen Mary, University of London ‡ Agena Ltd Abstract We Add to Reading List Source URL: www.agena.co.uk Language: English - Date: 2010-02-23 15:24:04 Bayesian statistics Bayesian network Normal distribution Probability distribution Statistical inference Bayesian inference Prior probability Kullback–Leibler divergence Conditional probability distribution Statistics Probability and statistics Statistical theory
23	Inference in Hybrid Bayesian Networks using dynamic discretisation Martin Neil†‡ , Manesh Tailor‡ and David Marquez† † Department of Computer Science, Queen Mary, University of London ‡ Agena Ltd Abstract We Add to Reading List Source URL: www.agenarisk.com Language: English - Date: 2010-02-23 15:24:04 Bayesian statistics Bayesian network Normal distribution Probability distribution Statistical inference Bayesian inference Prior probability Kullback–Leibler divergence Conditional probability distribution Statistics Probability and statistics Statistical theory
24	Journal of Machine Learning Research[removed]162 Submitted 6/08; Revised 10/08; Published 2/09 Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data Add to Reading List Source URL: www.jmlr.org Language: English - Date: 2009-02-17 18:30:20 Array programming languages Motorola PEBL Statistical models Bayesian statistics Scripting languages Dynamic Bayesian network Bayesian network SciPy NumPy Software Computing Science
25	David M. Blei Columbia University Department of Computer Science Department of Statistics Columbia University New York, NY Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2014-10-27 10:16:43 Latent Dirichlet allocation Dynamic topic model Pachinko allocation Machine learning Neural network Dirichlet process Bayesian inference Variational Bayesian methods Mixture model Statistics Statistical natural language processing Topic model
26	Dependency Parsing with Dynamic Bayesian Network Add to Reading List Source URL: aaai.org Language: English - Date: 2006-01-11 01:14:17 N-gram Bayesian inference Bayesian network Dependency grammar Graphical model Expectation–maximization algorithm Markov chain Probabilistic logic Hierarchical Bayes model Statistics Bayesian statistics Probability and statistics
27	Journal of Artificial Intelligence Research[removed]591 Submitted 11/08; published[removed]Optimal Value of Information in Graphical Models Andreas Krause Add to Reading List Source URL: www.select.cs.cmu.edu Language: English - Date: 2009-08-13 03:47:05 Statistical models Markov models Graphical models Bioinformatics Hidden Markov model Partially observable Markov decision process Bayesian network Dynamic programming Static single assignment form Statistics Mathematics Bayesian statistics
28	Beyond Keyword Search: Discovering Relevant Scientific Literature Khalid El-Arini Carlos Guestrin Add to Reading List Source URL: www.select.cs.cmu.edu Language: English - Date: 2011-06-19 06:28:38 Operations research Bayesian network Networks Dynamic programming Algorithm Function PageRank Mathematics Applied mathematics Statistics
29	Selecting Strategies for Infinite-Horizon Dynamic LIMIDs Marcel A.J. van Gerven Institute for Computing and Information Sciences Radboud University Nijmegen Toernooiveld[removed]ED Nijmegen, The Netherlands Add to Reading List Source URL: www.utia.cas.cz Language: English - Date: 2008-12-17 13:50:27 Mathematical optimization Equations Dynamic programming Operations research Optimal control Markov decision process Bayesian network Variable Bellman equation Statistics Mathematics Control theory
30	Exploiting Fully Observable and Deterministic Structures in Goal POMDPs Add to Reading List Source URL: www.ida.liu.se Language: English - Date: 2013-08-29 10:13:42 Stochastic control Partially observable Markov decision process Markov decision process Automated planning and scheduling Bayesian network FO S0 Finite-state machine Macro Statistics Dynamic programming Markov processes