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IEEEARES
2006
IEEE
14 years 5 months ago
Modeling Dependable Systems using Hybrid Bayesian Networks
A hybrid Bayesian Network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment the models are...
Martin Neil, Manesh Tailor, Norman E. Fenton, Davi...
CDC
2009
IEEE
167views Control Systems» more  CDC 2009»
14 years 3 months ago
Factoring Dynamic Bayesian Networks based on structural observability
— Dynamic Bayesian Networks (DBNs) provide a systematic framework for robust online monitoring of dynamic systems. This paper presents an approach for increasing the efficiency ...
Indranil Roychoudhury, Gautam Biswas, Xenofon D. K...
ACCV
2006
Springer
14 years 2 months ago
Double Regularized Bayesian Estimation for Blur Identification in Video Sequences
Blind blur identification in video sequences becomes more important. This paper presents a new method for identifying parameters of different blur kernels and image restoration in ...
Hongwei Zheng, Olaf Hellwich
AUSAI
2006
Springer
14 years 2 months ago
Learning Hybrid Bayesian Networks by MML
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
Rodney T. O'Donnell, Lloyd Allison, Kevin B. Korb
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
14 years 2 months ago
String transformation-based Bayesian classification or proteins
We describe a Markov chain Bayesian classification tool, SCS, that can perform data-driven classification of proteins and protein segments. Training data for interesting classific...
Timothy Meekhof, Gary W. Daughdrill, Robert B. Hec...