We have been using the concept map of the domain, enhanced with pedagogical concepts called learning objectives, as the overlay student model in our intelligent tutors for program...
The traditional approach to building Bayesian networks is to build the graphical structure using a graphical editor and then add probabilities using a separate spreadsheet for eac...
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...