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BMCBI
2007
172views more  BMCBI 2007»
13 years 6 months ago
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks
Background: Reverse engineering cellular networks is currently one of the most challenging problems in systems biology. Dynamic Bayesian networks (DBNs) seem to be particularly su...
Fulvia Ferrazzi, Paola Sebastiani, Marco Ramoni, R...
ICCV
1999
IEEE
14 years 7 months ago
A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and synthesizing figure motion has employed eit...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Ke...
ECCB
2003
IEEE
13 years 11 months ago
Gene networks inference using dynamic Bayesian networks
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
Bruno-Edouard Perrin, Liva Ralaivola, Aurél...
HYBRID
2000
Springer
13 years 9 months ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
AI
2006
Springer
13 years 6 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth