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JCB
2006
185views more  JCB 2006»
13 years 7 months ago
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
Andrew Golightly, Darren J. Wilkinson
AAAI
2008
13 years 9 months ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen
BMCBI
2010
170views more  BMCBI 2010»
13 years 7 months ago
Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks
Background: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed amo...
Alex Aussem, André Tchernof, Sergio Rodrigu...
NECO
2002
145views more  NECO 2002»
13 years 7 months ago
Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Aki Vehtari, Jouko Lampinen
IPMU
2010
Springer
13 years 6 months ago
Approximation of Data by Decomposable Belief Models
It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
Radim Jirousek