Project

Empirical Bayes Estimation of Parametric Gaussian Priors

Publisher

Supervisor

Location

Greater Copenhagen area

Empirical Bayes estimation can be used to estimate the parameters of a parametric prior. This project considers (i) models and computational methods for estimating a Gaussian prior that belongs to a specific class of priors, and (ii) applications in inverse problems and/or machine learning. Additional details are provided in the attached project description.

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Contact

Company / Organization

DTU Compute

Name

Martin Skovgaard Andersen

Position

Lektor

Mail

mskan@dtu.dk

Supervisor info

MSc in Mathematical Modelling and Computation

Supervisor

Martin Skovgaard Andersen

Co-supervisors

Per Christian Hansen

ECTS credits

30 - 35

Type

MSc thesis

Must be completed

02610 / 02612

Technical University of Denmark

For almost two centuries DTU, Technical University of Denmark, has been dedicated to fulfilling the vision of H.C. Ørsted – the father of electromagnetism – who founded the university in 1829 to develop and create value using the natural sciences and the technical sciences to benefit society.


Today, DTU is ranked as one of the foremost technical universities in Europe, continues to set new records in the number of publications, and persistently increases and develops our partnerships with industry, and assignments accomplished by DTU’s public sector consultancy.

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Anker Engelunds Vej 1
Bygning 101A
2800 Kgs. Lyngby

Denmark



Tlf. (+45) 45 25 25 25

CVR-nr. 30 06 09 46

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