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AROBOTS
2011
12 years 12 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
ICRA
2010
IEEE
104views Robotics» more  ICRA 2010»
13 years 3 months ago
Using model knowledge for learning inverse dynamics
— In recent years, learning models from data has become an increasingly interesting tool for robotics, as it allows straightforward and accurate model approximation. However, in ...
Duy Nguyen-Tuong, Jan Peters
ICASSP
2010
IEEE
13 years 3 months ago
A HMM-based speech synthesis system using a new glottal source and vocal-tract separation method
This paper introduces a HMM-based speech synthesis system which uses a new method for the Separation of Vocal-tract and LiljencrantsFant model plus Noise (SVLN). The glottal sourc...
Pierre Lanchantin, Gilles Degottex, Xavier Rodet
MICCAI
2004
Springer
14 years 5 months ago
3D Bayesian Regularization of Diffusion Tensor MRI Using Multivariate Gaussian Markov Random Fields
3D Bayesian regularization applied to diffusion tensor MRI is presented here. The approach uses Markov Random Field ideas and is based upon the definition of a 3D neighborhood syst...
Marcos Martín-Fernández, Carl-Fredri...
ICPR
2004
IEEE
14 years 6 months ago
Joint Spatial and Temporal Structure Learning for Task based Control
We present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. We review work o...
Hilary Buxton, Kingsley Sage