We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular...
Norm Aleks, Stuart Russell, Michael G. Madden, Dia...
We introduce a model of uncertainty where documents are not uniquely identified in a reference network, and some links may be incorrect. It generalizes the probabilistic approach ...
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
We motivate and study a generic relaxation of correctness of reactive and concurrent systems with respect to a temporal specification. We define a system to be fairly correct if...
Abstract. A model of human appearance is presented for efficient pose estimation from real-world images. In common with related approaches, a high-level model defines a space of co...
Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...