Gaussian Process Classification
Gaussian Process Classification is a probabilistic classification framework that employs Gaussian processes as the prior distribution over latent functions, distinguishing itself by modeling class probabilities through a likelihood function suitable for discrete outcomes.
174
Publications
13.1K
Citations
518
Authors
266
Institutions
Publications per year
2017–2026
62
174
1–5 of 174
518
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266
University of Oxford
Oxford, United Kingdom
9 h-index
28 publications
2.8K citations
University of Cambridge
Cambridge, United Kingdom
8 h-index
18 publications
1.5K citations

University of Edinburgh
Edinburgh, United Kingdom
5 h-index
6 publications
1.1K citations
Max Planck Institute for Biological Cybernetics
Tübingen, Germany
5 h-index
9 publications
3.1K citations

University of Macau
Macao, Macao
4 h-index
8 publications
223 citations
King's College London
London, United Kingdom
4 h-index
18 publications
1.5K citations

Universidad Autónoma de Madrid
Madrid, Spain
4 h-index
8 publications
184 citations

Aston University
Birmingham, United Kingdom
4 h-index
8 publications
554 citations
1–8 of 266
Repository · 21 publications · 923 citations
14
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5 publications · 171 citations
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Repository · 5 publications · 249 citations
5
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JMLR · 4 publications · 621 citations
4
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3 publications · 238 citations
3
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1–5