This paper outlines a radial basis function neural network approach to predict the failures in overhead distribution lines of power delivery systems. The RBF networks are trained ...
Grant Cochenour, Jerad Simon, Sanjoy Das, Anil Pah...
Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distr...
Jon M. Fincham, John R. Anderson, Shawn Betts, Jen...
GADTs have proven to be an invaluable language extension, a.o. for ensuring data invariants and program correctness. Unfortunately, they pose a tough problem for type inference: w...
Tom Schrijvers, Simon L. Peyton Jones, Martin Sulz...
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...