4981 search results - page 19 / 997 » Dependent Gaussian Processes |
ICML
2005
IEEE
16 years 17 days ago
2005
IEEE
This paper presents an algorithm to estimate simultaneously both mean and variance of a non parametric regression problem. The key point is that we are able to estimate variance l...
109
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NIPS
2004
15 years 1 months ago
2004
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
103
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ICASSP
2009
IEEE
15 years 6 months ago
2009
IEEE
We investigate a hybrid method which improves the quality of state inference and parameter estimation in blind deconvolution of a sparse source modeled by a Bernoulli-Gaussian pro...
117
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ICIP
2009
IEEE
14 years 9 months ago
2009
IEEE
The estimation of high-dimensional probability density functions (PDFs) is not an easy task for many image processing applications. The linear models assumed by widely used transf...
NIPS
2007
15 years 1 months ago
2007
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...