The MIT Press eBooks / 2005

Gaussian Processes for Machine Learning

Carl Edward Rasmussen, Christopher K. I. Williams

Popular and Landmark PapersProbabilistic ML

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.

10,486 citations0 influential

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### Paper attached as context
Title: Gaussian Processes for Machine Learning
Authors: Carl Edward Rasmussen, Christopher K. I. Williams
Year: 2005
Venue: The MIT Press eBooks
Categories: Popular and Landmark Papers, Probabilistic ML
Citations: 10,486
Paper URL: https://doi.org/10.7551/mitpress/3206.001.0001
Open PDF: Not available

Abstract:
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.

Learning resources:
- Google Scholar: Google Scholar references (https://scholar.google.com/scholar?q=Gaussian%20Processes%20for%20Machine%20Learning)
- OpenAlex: Paper page (https://doi.org/10.7551/mitpress/3206.001.0001)
- Papers with Code: Papers with Code search (https://paperswithcode.com/search?q=Gaussian%20Processes%20for%20Machine%20Learning)
- YouTube: YouTube explanations (https://www.youtube.com/results?search_query=Gaussian%20Processes%20for%20Machine%20Learning+paper+explained)