Gaussian Process

From Ioannis Kourouklides
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This page contains resources about Gaussian Processes (GP), including GP Classification and GP Regression (kriging).

Subfields and Concepts[edit]

Online Courses[edit]

Video Lectures[edit]

Lecture Notes[edit]

Books and Book Chapters[edit]

  • MacKay, D. J. (2003). "Chapter 45: Gaussian Processes". Information Theory, Inference and Learning Algorithms. Cambridge University Press.
  • Williams, C. K., & Rasmussen, C. E. (2006). Gaussian Processes for Machine Learning. MIT Press.
  • Murphy, K. P. (2012). "Chapter 15: Gaussian Processes". Machine Learning: A Probabilistic Perspective. MIT Press.
  • Barber, D. (2012). "Chapter 19: Gaussian Processes". Bayesian Reasoning and Machine Learning. Cambridge University Press.

Scholarly Articles[edit]

  • Rasmussen, C. E. (2004). Gaussian Processes in Machine Learning. In Advanced Lectures on Machine Learning. Springer Berlin Heidelberg.
  • Seeger, M. (2004). Gaussian processes for machine learning. International journal of neural systems14(02), 69-106.
  • Rasmussen, C. E., & Nickisch, H. (2010). Gaussian processes for machine learning (GPML) toolbox. Journal of Machine Learning Research11(Nov), 3011-3015.


See also[edit]

Other Resources[edit]