This project implements matrix completion for collaborative filtering using Gaussian Mixture Models (GMM) with the Expectation-Maximization (EM) algorithm. The project is specifically designed to ...

A python package for scalable Gaussian process regression, allowing for simultaneous inference of both a dataset's latent function and input-dependent noise profile. Originally developed for ...

Graphical Gaussian models with edge and vertex symmetries were introduced by Højsgaard & Lauritzen (2008), who gave an algorithm for computing the maximum likelihood estimate of the precision matrix ...

One of the fundamental operations in machine learning is computing the inverse of a square matrix. But not all matrices have an inverse. The most common way to check if a matrix has an inverse or not ...