Results 11 to 20 of about 160,175 (304)
Kernel Belief Propagation [PDF]
, 2011 We propose a nonparametric generalization of belief propagation, Kernel Belief Propagation (KBP), for pairwise Markov random fields. Messages are represented as functions in a reproducing kernel Hilbert space (RKHS), and message updates are simple linear operations in the RKHS.
Song, Le +4 more
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Sigma Point Belief Propagation [PDF]
IEEE Signal Processing Letters, 2014 5 pages, 1 ...
Meyer, Florian +2 more
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, 2007 We present an accurate numerical algorithm, called quantum belief propagation (QBP), for simulation of one-dimensional quantum systems at non-zero temperature. The algorithm exploits the fact that quantum effects are short-range in these systems at non-zero temperature, decaying on a length scale inversely proportional to the temperature. We compare to
M. B. Hastings +2 more
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Discriminated Belief Propagation
, 2007 Near optimal decoding of good error control codes is generally a difficult task. However, for a certain type of (sufficiently) good codes an efficient decoding algorithm with near optimal performance exists. These codes are defined via a combination of constituent codes with low complexity trellis representations.
Sorger, Uli
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A low density lattice decoder via non-parametric belief propagation [PDF]
, 2009 The recent work of Sommer, Feder and Shalvi presented a new family of codes called low density lattice codes (LDLC) that can be decoded efficiently and approach the capacity of the AWGN channel. A linear time iterative decoding scheme which is based on a
Danny Bickson +3 more
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Scene text recognition using similarity and a lexicon with sparse belief propagation. [PDF]
IEEE Trans Pattern Anal Mach Intell, 2009 Weinman JJ, Learned-Miller E, Hanson AR.
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Nonparametric belief propagation [PDF]
2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003 In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There exist inference algorithms for discrete approximations to these continuous distributions, but for the high-dimensional variables typically of interest, discrete inference ...
E.B. Sudderth +3 more
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IET Radar, Sonar & Navigation, 2023 The multi‐sensor multiple‐model generalised labelled multi‐Bernoulli filter (MS‐MM‐GLMB) is presented for tracking multiple manoeuvring targets. And we develop efficient implementation for computing multi‐target posterior.
Chenghu Cao, Yongbo Zhao
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Factorization in molecular modeling and belief propagation algorithms
Mathematical Biosciences and Engineering, 2023 Factorization reduces computational complexity, and is therefore an important tool in statistical machine learning of high dimensional systems. Conventional molecular modeling, including molecular dynamics and Monte Carlo simulations of molecular systems,
Bochuan Du , Pu Tian
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Calibrating Distributed Camera Networks Using Belief Propagation
EURASIP Journal on Advances in Signal Processing, 2007 We discuss how to obtain the accurate and globally consistent self-calibration of a distributed camera network, in which camera nodes with no centralized processor may be spread over a wide geographical area.
Richard J. Radke, Dhanya Devarajan
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