In recent years, there have been several proposals that extend the expressive power of Bayesian networks with that of relational models. These languages open the possibility for t...
We present a Bayesian blackboard system for temporal perception, applied to a minidomain task in musical scene analysis. It is similar to the classic Copycat architecture (Hofstad...
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
This paper deals with the analysis of temporal dependence in multivariate highfrequency time series data. The dependence structure between the marginal series is modelled through ...
Early, reliable detection of disease outbreaks is a critical problem today. This paper reports an investigation of the use of causal Bayesian networks to model spatio-temporal pat...
Gregory F. Cooper, Denver Dash, John Levander, Wen...