86 search results - page 10 / 18 » Conditioning Graphs: Practical Structures for Inference in B... |
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...
JMLR
2006
13 years 7 months ago
2006
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
UAI
1998
13 years 8 months ago
1998
The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system,...
TCBB
2008
13 years 7 months ago
2008
Recently, the concept of mutual information has been proposed for inferring the structure of genetic regulatory networks from gene expression profiling. After analyzing the limitat...
JMLR
2010
13 years 2 months 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...