markvdw

convgp

Convolutional Gaussian processes based on GPflow.

GParML

Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.

mml-autumn-2022

Materials for Autumn 2022 Mathematics for Machine Learning course.

RobustGP

Robust initialisation of inducing points in sparse variational GP regression models.

probinf-spring-2023

Probabilistic Inference Course, Department of Computing, Imperial College London, Spring 2023.

GPflow-inter-domain

Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables

gpflow-monitor

Methods to help with logging GPflow optimisation.

inference-plots

gp_upper

Upper bounds for Gaussian process regression marginal likelihoods.

GPflow

Gaussian processes in TensorFlow

GPflux

Deep GPs built on top of TensorFlow/Keras and GPflow

markvdw.github.io

Public webpage.

mltools

A collection of some miscellaneous tools for machine learning projects.

opt_tools

Tools for logging an optimisation procedure. Specially designed to work with scipy and GPflow.

datasets

A simple repo to organise datasets for machine learning experiments. Datasets are downloaded directly from source, and then processed, so there's never any ambiguity about pre-processing ever again.

gp-audio

GPLVMTry

Experimental GPLVM models

hugo-academic

The website designer for Hugo. Build and deploy a beautiful website in minutes :rocket:

observations

Tools for loading standard data sets in machine learning