This paper addresses the problem of tracking and diagnosing complex systems with mixtures of discrete and continuous variables. This problem is a difficult one, particularly when ...
Uri Lerner, Ronald Parr, Daphne Koller, Gautam Bis...
: A Bayesian distributed online change detection algorithm is proposed for monitoring a dynamical system by a wireless sensor network. The proposed solution relies on modelling the...
The purpose of this article is to present a method for industrial process diagnosis with Bayesian network, and more particularly with Conditional Gaussian Network (CGN). The inter...
Abstract— In this contribution, we propose an efficient collaborative strategy for online change detection, in a distributed sensor network. The collaborative strategy ensures t...
This paper proposes a diagnosis architecture that integrates consistency based diagnosis with induced time series classifiers, trying to combine the advantages of both methods. Co...