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

Torus kernel Sphere kernel Dragon manifold kernel

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.

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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
Paper Code
Pathwise Conditioning of Gaussian Processes
James T. Wilson,* Viacheslav Borovitskiy,* Alexander Terenin,* Peter Mostowsky,* and Marc Peter Deisenroth
JMLR 2021
Paper Code
Matérn Gaussian Processes on Riemannian Manifolds
Viacheslav Borovitskiy,* Alexander Terenin,* Peter Mostowsky,* and Marc Peter Deisenroth
NeurIPS 2020
Paper Code
Matérn Gaussian Processes on Graphs
Viacheslav Borovitskiy,* Iskander Azangulov,* Alexander Terenin,* Peter Mostowsky, Marc Peter Deisenroth, and Nicolas Durrande
AISTATS 2021
Paper Code
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
Paper Code
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
Paper Code

*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}}
Torus kernel Sphere kernel Dragon manifold kernel

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