Mark van der Wilk's Projects
Convolutional Gaussian processes based on GPflow.
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.
Upper bounds for Gaussian process regression marginal likelihoods.
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
Gaussian processes in TensorFlow
Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
Methods to help with logging GPflow optimisation.
Deep GPs built on top of TensorFlow/Keras and GPflow
Experimental GPLVM models
The website designer for Hugo. Build and deploy a beautiful website in minutes :rocket:
Public webpage.
A collection of some miscellaneous tools for machine learning projects.
Materials for Autumn 2022 Mathematics for Machine Learning course.
Tools for loading standard data sets in machine learning
Tools for logging an optimisation procedure. Specially designed to work with scipy and GPflow.
Probabilistic Inference Course, Department of Computing, Imperial College London, Spring 2023.
Robust initialisation of inducing points in sparse variational GP regression models.