README.md

Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces

This repository contains the LaTeX source for the PhD thesis written by Alexander Terenin. It also includes the scripts and data used for generating the figures in the thesis, which are created with a combination of TikZ and PGFPlots via the PGFPlotsX.jl Julia interface, as well as Blender. Code for running the experiments presented in the thesis can be found in each respective publication's repository, linked below.

Publications in this thesis

Efficiently Sampling Functions from Gaussian Process Posteriors James T. Wilson,* Viacheslav Borovitskiy,* Alexander Terenin,* Peter Mostowsky,* and Marc Peter Deisenroth ICML 2020

Pathwise Conditioning of Gaussian Processes James T. Wilson,* Viacheslav Borovitskiy,* Alexander Terenin,* Peter Mostowsky,* and Marc Peter Deisenroth JMLR 2021

Matérn Gaussian Processes on Riemannian Manifolds Viacheslav Borovitskiy,* Alexander Terenin,* Peter Mostowsky,* and Marc Peter Deisenroth NeurIPS 2020

Matérn Gaussian Processes on Graphs Viacheslav Borovitskiy,* Iskander Azangulov,* Alexander Terenin,* Peter Mostowsky, Marc Peter Deisenroth, and Nicolas Durrande AISTATS 2021

Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels Noémie Jaquier, Viacheslav Borovitskiy, Andrei Smolensky, Alexander Terenin, Tamim Asfour, and Leonel Rozo CoRL 2021

Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels Michael John Hutchinson,* Alexander Terenin,* Viacheslav Borovitskiy,* So Takao,* Yee Whye Teh, and Marc Peter Deisenroth NeurIPS 2021

*Equal contribution

Citation

@phdthesis{terenin22,
    author = {Alexander Terenin},
    school = {Imperial College London},
    title = {Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces},
    year = {2022}}