Bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with ef?cient algorithms for inference and learning. Ear...
Tanzeem Choudhury, James M. Rehg, Vladimir Pavlovi...
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
We present generative models dedicated to face recognition. Our models consider data extracted from color face images and use Bayesian Networks to model relationships between diffe...
This paper describes how high level biological knowledge obtained from ontologies such as the Gene Ontology (GO) can be integrated with low level information extracted from a Baye...
Abstract. This paper describes the process by which we are constructing an intelligent tutoring system (ERST) designed to improve learners’ external representation (ER) selection...