Previous studies have demonstrated that encoding a Bayesian network into a SAT-CNF formula and then performing weighted model counting using a backtracking search algorithm can be...
Particle filtering (PF) for dynamic Bayesian networks (DBNs) with discrete-state spaces includes a resampling step which concentrates samples according to their relative weight in ...
Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...
Background: In many approaches to the inference and modeling of regulatory interactions using microarray data, the expression of the gene coding for the transcription factor is co...
Particle filtering algorithms can be used for the monitoring of dynamic systems with continuous state variables and without any constraints on the form of the probability distribu...