Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
This paper considers the problem of performing decentralised coordination of low-power embedded devices (as is required within many environmental sensing and surveillance applicat...
Alessandro Farinelli, Alex Rogers, Adrian Petcu, N...
Any performance evaluation of broadband networks requires modeling of the actual network traffic. Since multimedia services and especially MPEG coded video streams are expected to...
Anastasios D. Doulamis, Nikolaos D. Doulamis, Stef...
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...