Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
— Recent studies have shown that many real networks follow the power-law distribution of node degrees. Instead of random connectivity, however, power-law connectivity suffers fro...
Modeling and estimation of switching activities remain to be important problems in low-power design and fault analysis. A probabilistic Bayesian Network based switching model can ...
Creating accurate models of information systems is an important but challenging task. It is generally well understood that such modeling encompasses general scientific issues, bu...
Ulrik Franke, Pontus Johnson, Robert Lagerströ...
There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...