/Gaussian-Process

Fun with Gaussian processes.

Primary LanguageJupyter NotebookMIT LicenseMIT

Gaussian-Process

Currently there are 3 notebooks in this repo.

Introduction to the Gaussian Process

This notebook provides an introduction to GPs and code to generate samples from GPs with different mean and covariance parameters. The notebook uses rise to generate slides. Click on the binder link below to view slides.

Binder

Covariance Functions

This notebook illustrates the differences between the squared exponential and Matérn covariance functions.
Covariance Functions

Mathematical Derivations

This notebook provides the derivations of the predictions (interpolated values) from a Gaussian process fit.
Mathematical Derivations