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Junction tree algorithm

Known as: Junction-tree algorithm 
The junction tree algorithm (also known as 'Clique Tree') is a method used in machine learning to extract marginalization in general graphs. In… (More)
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Topic mentions per year

Topic mentions per year

1996-2017
024619962017

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10 relations
Bayesian networkBelief propagationCycleDecomposition method
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Related mentions per year

Related mentions per year

1936-2018
19401960198020002020
Junction tree algorithm
Machine learning
Decomposition method
Bayesian network
Graphical model
Graph

Papers overview

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2017
2017
Counting and Conjunctive Queries in the Lifted Junction Tree Algorithm
Standard approaches for inference in probabilistic formalisms with first-order constructs include lifted variable elimination… (More)
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2013
2013
The Inclusion-Exclusion Rule and its Application to the Junction Tree Algorithm
In this paper, we consider the inclusion-exclusion rule – a known yet seldom used rule of probabilistic inference. Unlike the… (More)
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2008
2008
Junction Tree Algorithm
In the previous scribes, we introduced general objects used in graphical models as well message passing schemes such as the sum… (More)
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2007
2007
Anomaly Based Intrusion Detection Based on the Junction Tree Algorithm
The aim of this paper is to present a methodology for the attacks recognition during the normal activities in the system. Since… (More)
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2004
2004
A DBN inference algorithm using junction tree
Dynamic bayesian networks (DBNs) is a compact representation of complex stochastic processes and has been used for many purposes… (More)
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Highly Cited
2002
Highly Cited
2002
Dynamic Bayesian Networks : Representation , Inference and Learning
Dynamic Bayesian Networks: Representation, Inference and Learning by Kevin Patrick Murphy Doctor of Philosophy in Computer… (More)
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Highly Cited
2000
Highly Cited
2000
Variational Approximations between Mean Field Theory and the Junction Tree Algorithm
Recently, variational approximations such as the mean field approximation have received much interest. We extend the standard… (More)
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Highly Cited
2000
Highly Cited
2000
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
  • Arnaud Doucetz, Nando de Freitasy, Kevin Murphyy, Stuart Russelly
  • 2000
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow… (More)
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Highly Cited
2000
Highly Cited
2000
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow… (More)
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Highly Cited
1996
Highly Cited
1996
A sufficiently fast algorithm for finding close to optimal junction trees
An algorithm is developed for finding a close to optimal junction tree of a given graph G. The algorithm has a worst case… (More)
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