Correlated product of experts for sparse Gaussian process regression

DOI10.1007/s10994-022-06297-3arXiv2112.09519OpenAlexW4318020634MaRDI QIDQ6161201

Manuel Schürch, Dario Filippo Azzimonti, Alessio Benavoli, Marco Zaffalon

Publication date: 27 June 2023

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2112.09519

zbMATH Keywords

Gaussian processesexpert fusionprobabilistic regression

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Nested kriging predictions for datasets with a large number of observations
• Nested aggregation of experts using inducing points for approximated Gaussian process regression
• Recursive estimation for sparse Gaussian process regression
• Sparse On-Line Gaussian Processes
• Training Products of Experts by Minimizing Contrastive Divergence
• A general framework for Vecchia approximations of Gaussian processes
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