Journal article
Sequential auxiliary particle belief propagation
- Abstract:
-
This paper discloses a novel algorithm for efficient inference in undirected graphical models using Sequential Monte Carlo (SMC) based numerical approximation techniques. The methodology developed, titled "Auxiliary Particle Belief Propagation", extends the applicability of the much celebrated (Loopy) Belief Propagation (LBP) algorithm to non-linear, non-Gaussian models, whilst retaining a computational cost that is linear in the number of sample points (or particles). Furthermore, we provide...
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- Publication status:
- Published
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- Publisher copy:
- 10.1109/ICIF.2005.1591923
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Authors
Bibliographic Details
- Journal:
- 2005 7th International Conference on Information Fusion (FUSION), Vols 1 and 2
- Volume:
- 1
- Pages:
- 705-711
- Publication date:
- 2005-01-01
- DOI:
- Source identifiers:
-
172724
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
pubs:172724
- UUID:
-
uuid:fcc2473b-1967-4e67-8aa1-e763a7c605dd
- Local pid:
- pubs:172724
- Deposit date:
- 2012-12-19
Terms of use
- Copyright date:
- 2005
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