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Title:Image modelling with position-encoding dynamic trees
Authors: Amos Storkey ; Chris Williams
Date: 2003
Publication Title:IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Publisher:IEEE Computer Society
Publication Type:Journal Article Publication Status:Published
Volume No:25(7) Page Nos:859-872
Dynamic trees are mixtures of tree structured belief networks. They solve some of the problems of fixed tree networks at the cost of making exact inference intractable. For this reason approximate methods such as sampling or mean field approaches have been used. However, mean field approximations assume a factorised distribution over node states. Such a distribution seems unlikely in the posterior, as nodes are highly correlated in the prior. Here a structured variational approach is used, where the posterior distribution over the non-evidential nodes is itself approximated by a dynamic tree. It turns out that this form can be used tractably and efficiently. The result is a set of update rules which can propagate information through the network to obtain both a full variational approximation, and the relevant marginals.
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Bibtex format
author = { Amos Storkey and Chris Williams },
title = {Image modelling with position-encoding dynamic trees},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
publisher = {IEEE Computer Society},
year = 2003,
volume = {25(7)},
pages = {859-872},
doi = {10.1109/TPAMI.2003.1206515},
url = {},

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