175 search results - page 3 / 35 » Learning Continuous Time Bayesian Networks |
CORR
2012
Springer
12 years 2 months ago
2012
Springer
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
NIPS
2008
13 years 8 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
ICML
1998
IEEE
14 years 7 months ago
1998
IEEE
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
UAI
1998
13 years 8 months ago
1998
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
PERVASIVE
2009
Springer
14 years 1 months ago
2009
Springer
This paper presents novel methodologies for the analysis of continuous cellular tower data from 215 randomly sampled subjects in a major urban city. We demonstrate the potential of...