307 search results - page 2 / 62 » A Dynamic Bayesian Network Approach to Tracking Using Learne... |
CIRA
2007
IEEE
13 years 12 months ago
2007
IEEE
— Learning motion models of a moving object is a challenge for autonomous robots. We address the particular instance of parameter learning when tracking object motions in a switc...
NN
1997
Springer
13 years 9 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
NIPS
2004
13 years 6 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...
NIPS
2008
13 years 7 months ago
2008
Many nonlinear dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
ECCB
2003
IEEE
13 years 10 months ago
2003
IEEE
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...