Mon 20 August 2018

VFE approximation for Gaussian processes, the gory details
This post gives the VFE Gaussian process derivation in detail. The implementation details are given in another post. \(\newcommand{\X …

Mon 09 July 2018

Mauna Loa Example 2: Incorporating atmospheric measurements
This GP example shows how to: Fit fully Bayesian GPs with NUTS Model inputs which are themselves uncertain (uncertainty in …

Wed 13 June 2018

Mauna Loa Example 2: Ice core data
This GP example shows how to: Fit fully Bayesian GPs with NUTS Model inputs which are themselves uncertain (uncertainty in …

Sat 12 August 2017

Looking at the Keeling Curve with GPs in PyMC3
This post discusses modeling the CO2 measurments at Mauna Loa using Gaussian processes in PyMC3.

Wed 26 July 2017

GP module refactor
An outline of my refactor of the GP module so far.

Mon 10 July 2017

GPs with non-Normal likelihoods in PyMC3
Gaussian processes can be used with non-Gaussian likelihoods. In this case, the latent variables cannot be marginalized away.

Thu 29 June 2017

PyMC3 FITC/VFE implementation notes
This post shows in detail how FITC and VFE is implemented in PyMC3.

Wed 28 June 2017

FITC and VFE
Two general Gaussian Process approximation methods are FITC (fully independent training conditional), and VFE (variational free energy).

Thu 01 June 2017

Inducing point methods to speed up GPs
Another main avenue for speeding up GPs is inducing point methods, or sparse GPs.

Mon 29 May 2017

Speeding up GPs with special kernel matrix structure
Linear algebra tricks to speed up GPs

Thu 25 May 2017

Gaussian processes models
A from-the-ground-up description of Bayesian gaussian process models.