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SAC
2008
ACM
14 years 9 months ago
Bayesian inference for a discretely observed stochastic kinetic model
The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical data are intrinsically stochastic and tend to be observ...
Richard J. Boys, Darren J. Wilkinson, Thomas B. L....
APN
2008
Springer
14 years 11 months ago
MC-SOG: An LTL Model Checker Based on Symbolic Observation Graphs
Model checking is a powerful and widespread technique for the verification of finite distributed systems. However, the main hindrance for wider application of this technique is the...
Kais Klai, Denis Poitrenaud
AUTOMATICA
2006
112views more  AUTOMATICA 2006»
14 years 9 months ago
Joint identification of plant rational models and noise distribution functions using binary-valued observations
System identification of plants with binary-valued output observations is of importance in understanding modeling capability and limitations for systems with limited sensor inform...
Le Yi Wang, Gang George Yin, Ji-Feng Zhang
ICASSP
2011
IEEE
14 years 1 months ago
On selecting the hyperparameters of the DPM models for the density estimation of observation errors
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...
ICIP
2006
IEEE
15 years 11 months ago
Variational Unsupervised Segmentation of Multi-Look Complex Polarimetric Images using a Wishart Observation Model
We address unsupervised variational segmentation ofmulti-look complex polarimetric images using a Wishart observation model via level sets. The methods consists of minimizing a fu...
Ismail Ben Ayed, Amar Mitiche, Ziad Belhadj