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Everything about Gaussian process
Statistical model
In probability theory and statistics, a Gaussian process is a stochastic process, such that every finite collection of those random variables has a multivariate normal distribution. The distribution of a Gaussian process is the joint distribution of all those random variables, and as such, it is a distribution over functions on its index set, e.g. time or space. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Gaussian processA 5-minute orientation
- Skim a recent paper: An Intuitive Tutorial to Gaussian Process RegressionInfluential work since 2022
- Pick up a classic book: Gaussian processes for machine learningThe most-reprinted book on the subject
- Read the landmark paper: Diagnostics for Gaussian Process EmulatorsCited 304 times
- Go sideways: Bayesian interpretation of kernel regularizationA closely related topic
- Go sideways: Neural network Gaussian processA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Diagnostics for Gaussian Process Emulators
Gaussian process cosmography
Gaussian process occupancy maps
Gaussian Process Morphable Models
Variational Gaussian process classifiers
Bagging for Gaussian process regression
Gaussian process dynamic programming
Echo State Gaussian Process
🆕 Influential since 2022
📚 Books worth reading
Gaussian processes for machine learningCarl Edward Rasmussen · 2005
Large Deviations for Gaussian QueuesMichel Mandjes · 2007- 📕Handbook for Applied ModelingJamie D. Riggs, Trent L. Lalonde · 2017
- 📕Stable Non-Gaussian Random ProcessesGennady Samoradnitsky · 2017
Markov processes, Gaussian processes, and local timesMichael B. Marcus · 2006- 📕Level Sets and Extrema of Random Processes and FieldsJean-Marc Azais, Mario Wschebor · 2008
- 📕Gaussian step-pressure loading of rigid viscoplastic platesRobert J. Hayduk · 1978
- 📕Gaussian Processes on TreesAnton Bovier · 2016
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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- Kriging In statistics, originally in geostatistics, kriging or Kriging (/ˈkriːɡɪŋ/), also known as Gaussian process regression, is a method of interpolation based…
- Kernel methods for vector output Kernel methods are a well-established tool to analyze the relationship between input data and the corresponding output of a function. Kernels encapsulate…
- Bayesian quadrature Bayesian quadrature is a method for approximating intractable integration problems. It falls within the class of probabilistic numerical methods. Bayesian…
- Comparison of Gaussian process software This is a comparison of statistical analysis software that allows doing inference with Gaussian processes often using approximations. This article is written…