38 search results - page 2 / 8 » Mocapy - A toolkit for inference and learning in dynamic B... |
CVPR
2000
IEEE
14 years 6 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...
METMBS
2003
13 years 6 months ago
2003
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
HYBRID
2000
Springer
13 years 8 months ago
2000
Springer
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
ICML
2005
IEEE
14 years 5 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...