Maintaining the integrity of large-scale networks is becoming an increasingly daunting task as networks expand at an unprecedented rate. The majority of present network monitoring...
This paper presents Bayesian edge inference (BEI), a
single-frame super-resolution method explicitly grounded in
Bayesian inference that addresses issues common to existing
meth...
Bryan S. Morse, Dan Ventura, Kevin D. Seppi, Neil ...
— 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...