1293 search results - page 17 / 259 » Modelling Smooth Paths Using Gaussian Processes |
ICML
2010
IEEE
13 years 11 months ago
2010
IEEE
We combine Bayesian online change point detection with Gaussian processes to create a nonparametric time series model which can handle change points. The model can be used to loca...
CVPR
2006
IEEE
14 years 12 months ago
2006
IEEE
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
ECML
2006
Springer
14 years 1 months ago
2006
Springer
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
RSS
2007
13 years 11 months ago
2007
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
AROBOTS
2011
13 years 4 months ago
2011
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...