— Probabilistic models were developed to provide predictive distributions of daily maximum surface level ozone concentrations. Five forecast models were compared at two stations ...
Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
Our argumentation system, NAG, uses Bayesian networks in a user model and in a normative model to assemble and assess arguments which balance persuasiveness with normative correct...
—This paper proposes the sequential context inference (SCI) algorithm for Markov random field (MRF) image analysis. This algorithm is designed primarily for fast inference on an...
In this paper we consider the problem of inferring link-level loss rates from end-to-end multicast measurements taken from a collection of trees. We give conditions under which lo...
Tian Bu, Nick G. Duffield, Francesco Lo Presti, Do...