This article is a critical review of computational techniques used to model, analyse and simulate signalling networks. We propose a conceptual framework, and discuss the role of s...
—In this paper, we analyze restrictions of traditional models affecting the accuracy of analytical prediction of the execution time of collective communication operations. In par...
Alexey L. Lastovetsky, Vladimir Rychkov, Maureen O...
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
The increasingly common practice of replicating datasets and using resources as distributed data stores in Grid environments has led to the problem of determining which replica ca...
In this paper, we propose a model for representing and predicting distances in large-scale networks by matrix factorization. The model is useful for network distance sensitive app...