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INFOCOM
2010
IEEE
14 years 8 months ago
Bayesian Inference for Localization in Cellular Networks
—In this paper, we present a general technique based on Bayesian inference to locate mobiles in cellular networks. We study the problem of localizing users in a cellular network ...
Hui Zang, François Baccelli, Jean Bolot
AAAI
2007
15 years 3 days ago
Macroscopic Models of Clique Tree Growth for Bayesian Networks
In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach to characterizing ...
Ole J. Mengshoel
AAAI
2011
13 years 9 months ago
Mean Field Inference in Dependency Networks: An Empirical Study
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
Daniel Lowd, Arash Shamaei
BMCBI
2010
229views more  BMCBI 2010»
14 years 10 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
IJAR
2006
98views more  IJAR 2006»
14 years 9 months ago
Inference in hybrid Bayesian networks with mixtures of truncated exponentials
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for solving hybrid Bayesian networks. Any probability density function can be approximated...
Barry R. Cobb, Prakash P. Shenoy