95 search results - page 3 / 19 » Learning Non-Stationary Dynamic Bayesian Networks |
ICPR
2002
IEEE
14 years 6 months ago
2002
IEEE
Bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with ef?cient algorithms for inference and learning. Ear...
CVPR
2000
IEEE
14 years 7 months ago
2000
IEEE
Design and development of novel human-computer interfaces poses a challenging problem: actions and intentions of users have to be inferred from sequences of noisy and ambiguous mu...
ICML
2005
IEEE
14 years 6 months ago
2005
IEEE
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
BMCBI
2010
13 years 5 months ago
2010
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
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...