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Expectation propagation
Results: 38

#	Item
11	Expectation Propagation for Continuous Time Bayesian Networks Uri Nodelman Stanford University Add to Reading List Source URL: www.cs.ucr.edu Language: English - Date: 2005-06-07 19:53:02
12	TAP Gibbs Free Energy, Belief Propagation and Sparsity Lehel Csat´o and Manfred Opper Neural Computing Research Group School of Engineering and Applied Science Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-04-24 01:39:22 Normal distribution Belief propagation Kullback–Leibler divergence Bayesian network Expectation–maximization algorithm Gaussian function Statistics Graphical models Bayesian statistics
13	Probabilistic Modelling and Reasoning School of Informatics, University of Edinburgh Instructor: Prof Chris Williams September 2012 Assessment By formal examination (80%) and one assignment (20%). Add to Reading List Source URL: www.inf.ed.ac.uk Language: English - Date: 2012-08-31 08:26:57 Statistical models Networks Probability theory Bayesian network Expectation–maximization algorithm Hidden Markov model Bayesian inference Markov random field Belief propagation Statistics Graphical models Bayesian statistics
14	C HRISTIAN R. S HELTON University of California, Riverside Department of Computer Science & Engineering 327 Chung Hall Riverside, CA 92521 Add to Reading List Source URL: www.cs.ucr.edu Language: English - Date: 2014-12-15 19:31:19 Computational statistics Expectation propagation International Conference on Machine Learning Conference on Neural Information Processing Systems Daphne Koller Ambient intelligence Machine learning Artificial intelligence Learning
15	Expectation Propagation for Continuous Time Bayesian Networks Uri Nodelman Stanford University Add to Reading List Source URL: robotics.stanford.edu Language: English - Date: 2005-06-05 21:42:48 Graphical models Markov processes Probability theory Exponentials Belief propagation Coding theory Continuous-time Markov process Normal distribution Expectation–maximization algorithm Statistics Mathematics Probability and statistics
16	Error-Bounded Probabilistic Graphical Model Simplification by Scott A. Wahl A proposal submitted in partial fulfillment Add to Reading List Source URL: www.cs.montana.edu Language: English - Date: 2014-10-27 15:50:48 Statistical models Networks Bayesian networks Prognostics Expectation–maximization algorithm Factor graph Belief propagation Statistics Bayesian statistics Graphical models
17	1 Unsupervised Learning of Probabilistic Object Models (POMs) for Object Classification, Segmentation and Recognition using Knowledge Propagation Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2009-04-15 12:42:52 Missing data Statistics Estimation theory Expectation–maximization algorithm
18	Journal of Machine Learning Research[removed]2173 Submitted 2/10; Revised 8/10; Published 8/10 libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models Add to Reading List Source URL: www.jmlr.org Language: English - Date: 2010-08-23 18:11:12 Mathematics Belief propagation Factor graph Bayesian network Markov random field Conditional random field Gibbs sampling Expectation–maximization algorithm Tree decomposition Graphical models Graph theory Statistics
19	INVITED PAPER The Factor Graph Approach to Model-Based Signal Processing Factor graphs can model complex systems and help to design effective Add to Reading List Source URL: fab.cba.mit.edu Language: English - Date: 2012-04-27 09:05:47 Statistics Belief propagation Coding theory Probability theory Factor graph Logarithm Expectation–maximization algorithm Graph theory Mathematics Graphical models
20	Journal of Machine Learning Research[removed]1736 Submitted 12/09; Revised 4/10; Published 5/10 FastInf: An Efficient Approximate Inference Library Ariel Jaimovich Add to Reading List Source URL: www.jmlr.org Language: English - Date: 2010-05-17 17:54:22 Bayesian statistics Statistical models Probability theory Networks Belief propagation Bayesian network Probabilistic relational model Expectation–maximization algorithm Machine learning Statistics Graphical models Probability