Gaussian Process Regression is a non-parametric Bayesian regression method that models the distribution over functions directly, using a Gaussian process as the prior distribution over the function space, where correlations between observed data points are determined by a covariance function or kernel.
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Smoking Prevalence and Cigarette Consumption in 187 Countries, 1980-2012
Marie Ng, Michael K Freeman, Thomas Fleming et al. · JAMA · 2014 · 1.6K citations
Public Health, Health Sciences, Population Health Sciences +15
Sparse Gaussian Processes using Pseudo-inputs
Edward Snelson, Zoubin Ghahramani · 2005 · 1.3K citations
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North Carolina State University
Raleigh, United States
35 h-index
65 publications
6.3K citations
University of Cambridge
Cambridge, United Kingdom
34 h-index
126 publications
8.5K citations
University of Oxford
Oxford, United Kingdom
32 h-index
133 publications
16.2K citations
Imperial College London
London, United Kingdom
26 h-index
100 publications
10.6K citations
University College London
London, United Kingdom
24 h-index
66 publications
10.7K citations
University of Sheffield
Sheffield, United Kingdom
23 h-index
75 publications
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Centre National de la Recherche Scientifique
Paris, France
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Massachusetts Institute of Technology
Cambridge, United States
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Repository · 82 publications · 3K citations
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