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JMLR
2010
155views more  JMLR 2010»
13 years 5 months ago
Bayesian Gaussian Process Latent Variable Model
We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensionality reduction. This method...
Michalis Titsias, Neil D. Lawrence
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 11 months ago
A bayesian mixture model with linear regression mixing proportions
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
IROS
2008
IEEE
211views Robotics» more  IROS 2008»
14 years 5 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
AAAI
1998
14 years 9 days ago
Procedural Help in Andes: Generating Hints Using a Bayesian Network Student Model
One of the most important problems for an intelligent tutoring system is deciding how to respond when a student asks for help. Responding cooperatively requires an understanding o...
Abigail S. Gertner, Cristina Conati, Kurt VanLehn
IPMI
2005
Springer
14 years 11 months ago
Bayesian Population Modeling of Effective Connectivity
Abstract. A hierarchical model based on the Multivariate Autoregessive (MAR) process is proposed to jointly model neurological time-series collected from multiple subjects, and to ...
Eric R. Cosman Jr., William M. Wells III