Conference item icon

Conference item

Particle filters for graphical models

Abstract:

This paper discloses a novel algorithm for efficient inference in undirected graphical models using Sequential Monte Carlo (SMC) based numerical approximation techniques. The developed methodology extends the applicability of the much celebrated Loopy Belief Propagation (LBP) algorithm to nonlinear, non-Gaussian models, whilst retaining a computational cost that is linear in the number of sample points (or particles). The work presented is thus a general framework that can be applied to a ple...

Expand abstract

Actions


Access Document


Publisher copy:
10.1109/NSSPW.2006.4378820
Host title:
NSSPW - Nonlinear Statistical Signal Processing Workshop 2006
Publication date:
2006-01-01
DOI:
ISBN-10:
1424405815
ISBN-13:
9781424405817
Pubs id:
pubs:172752
UUID:
uuid:05590128-a93f-4998-96a3-61ef2805e647
Local pid:
pubs:172752
Source identifiers:
172752
Deposit date:
2012-12-19

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP