447 search results - page 34 / 90 » Explaining inferences in Bayesian networks |
111
Voted
IJON
2010
15 years 2 months ago
2010
Originally devoted to specific applications such as biology, medicine and demography, duration models are now widely used in economy, finance or reliability. Recent works in var...
140
Voted
CJ
2010
15 years 28 days ago
2010
an be used to abstract away from the physical reality by describing it as components that exist in discrete states with probabilistically invoked actions that change the state. The...
140
Voted
JMLR
2010
14 years 10 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...
157
Voted
JMLR
2010
14 years 10 months ago
2010
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
155
Voted
NIPS
2004
15 years 4 months ago
2004
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...