We propose a novel approach for statistical risk modeling of network attacks that lets an operator perform risk analysis using a data model and an impact model on top of an attack ...
In this paper we investigate the fault diagnosis problem in IP networks. We provide a lower bound on the average number of probes per edge using variational inference technique pro...
Rajesh Narasimha, Souvik Dihidar, Chuanyi Ji, Stev...
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...