68 search results - page 2 / 14 » On the robustness of Bayesian networks to learning from non-... |
SARA
2007
Springer
13 years 11 months ago
2007
Springer
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
NIPS
2000
13 years 6 months ago
2000
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
BMCBI
2010
13 years 5 months ago
2010
Background: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed amo...
IDA
2003
Springer
13 years 10 months ago
2003
Springer
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
JMLR
2010
13 years 3 days ago
2010
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...