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ICML
2010
IEEE
13 years 9 months ago
Gaussian Process Change Point Models
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...
Yunus Saatci, Ryan Turner, Carl Edward Rasmussen
BMVC
2010
13 years 6 months ago
Local Gaussian Processes for Pose Recognition from Noisy Inputs
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Martin Fergie, Aphrodite Galata
ICCV
2011
IEEE
12 years 8 months ago
Gaussian Process Regression Flow for Analysis of Motion Trajectories
Recognition of motions and activities of objects in videos requires effective representations for analysis and matching of motion trajectories. In this paper, we introduce a new r...
Kihwan Kim, Dongryeol Lee, Irfan Essa
NIPS
2001
13 years 10 months ago
Learning a Gaussian Process Prior for Automatically Generating Music Playlists
This paper presents AutoDJ: a system for automatically generating music playlists based on one or more seed songs selected by a user. AutoDJ uses Gaussian Process Regression to le...
John C. Platt, Christopher J. C. Burges, S. Swenso...
JMLR
2010
147views more  JMLR 2010»
13 years 3 months ago
Gaussian Processes for Machine Learning (GPML) Toolbox
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
Carl Edward Rasmussen, Hannes Nickisch