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Thesis

Gaussian process arc lengths, functional regression and applications

Abstract:

This thesis presents novel functional regression methods for non-linear data and develops core Gaussian Process theory for arc lengths. The need for richer functional regression methods and theory around Gaussian Process arc lengths is established in the introduction.

Chapter 1 commences with the requisite background material and Chapter 2 works through the fundamentals of probability, highlighting key messages with a worked example. Gaussian Processes are introduced in Chapter 3, d...

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Division:
MPLS
Department:
Engineering Science
Role:
Author

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Role:
Supervisor
Role:
Supervisor
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
UUID:
uuid:b602e259-d4eb-4177-8937-18f733fe71e6
Deposit date:
2019-07-06

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