Exact or approximate inference in graphical models: why the choice is dictated by the treewidth, and how variable elimination can be exploited-Reference-Cited by-同舟云学术

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Exact or approximate inference in graphical models: why the choice is dictated by the treewidth, and how variable elimination can be exploited

Published:2019-06 Issue:2 Volume:61 Page:89-133
ISSN:1369-1473
Container-title:Australian & New Zealand Journal of Statistics
language:en
Short-container-title:Aust. N. Z. J. Stat.

Author:

Peyrard N.¹,Cros M.‐J.¹,Givry S.¹,Franc A.²,Robin S.³⁴,Sabbadin R.¹,Schiex T.¹,Vignes M.⁵

Affiliation:

1. INRA UR 875 MIAT Chemin de Borde Rouge 31326Castanet‐Tolosan France

2. INRA UMR 1202 Biodiversité, Gènes et Communautés 69, route d'Arcachon, Pierroton 33612Cestas Cedex France

3. AgroParisTech UMR 518 MIA 16 rue Claude Bernard Paris 5e France

4. INRA, UMR 518 MIA 16 rue Claude Bernard Paris 5e France

5. Institute of Fundamental Sciences Massey University Palmerston North New Zealand

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/anzs.12257

Reference130 articles.

1. Completing Networks Using Observed Data

2. An Approximate Minimum Degree Ordering Algorithm

3. Andres B. Beier T.&Kappes J.H.(2012).OpenGM: A C++ library for discrete graphical models. arXiv 1206.0111.

4. Andres B. Beier T.&Kappes J.H.(2013).OpenGM benchmark ‐ CVPR'2013 section. Available from URL:http://hci.iwr.uni-heidelberg.de/opengm2?l0=benchmark.

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