SheffieldML/vargplvm

This repository contains both MATLAB and R code for implementing the Bayesian GP-LVM. The MATLAB code is in the subdirectory vargplvm, the R code in vargplvmR. For a quick description and sample videos / demos check: http://git.io/A3Uv The Bayesian GP-LVM (Titsias and Lawrence, 2010) is an extension of the traditional GP-LVM where the latent space is approximately marginalised out in a variational fashion (hence the prefix'vargplvm'). Let us denote \mathbf{Y} as a matrix of observations (here called outputs) with dimensions n \times p, where n rows correspond to datapoints and p columns to dimensions.