Markov chain monte carlo methods vs. variational inference approaches in posterior density estimation for bayesian neural networks

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dc.contributor.authorChabumba, Daisy Reneilwe
dc.contributor.supervisorMlambo, Farai
dc.contributor.supervisorChironda, Cyril
dc.date.accessioned2026-10-16T17:07:52Z
dc.date.issued2025-12
dc.descriptionA research report submitted in partial fulfillment of the requirements for the degree of Master of Science, to the Faculty of Science, School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, 2025
dc.description.abstractNot Available
dc.description.sponsorshipNational e-Science Postgraduate Teaching & Training Platform (NEPTTP)
dc.description.submitterMMM2026
dc.facultyFaculty of Science
dc.identifier0000-0003-1760-5332
dc.identifier.citationChabumba, Daisy Reneilwe. (2025). Markov chain monte carlo methods vs. variational inference approaches in posterior density estimation for bayesian neural networks. [Master's dissertation, University of the Witwatersrand, Johannesburg]. WIReDSpace. https://hdl.handle.net/10539/50155
dc.identifier.urihttps://hdl.handle.net/10539/50155
dc.language.isoen
dc.publisherUniversity of the Witwatersrand, Johannesburg
dc.rights©2025 University of the Witwatersrand, Johannesburg. All rights reserved. The copyright in this work vests in the University of the Witwatersrand, Johannesburg. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of University of the Witwatersrand, Johannesburg.
dc.rights.holderUniversity of the Witwatersrand, Johannesburg
dc.schoolSchool of Computer Science and Applied Mathematics
dc.subjectBayesian Inference (BI)
dc.subjectBayesian Neural Network (BNN)
dc.subjectMarkovChainMonte Carlo(MCMC)
dc.subjectPosterior Distribution
dc.subjectRandomWalkMetropolis(RWM)
dc.subjectVariational Inference (VI)
dc.subjectUCTD
dc.subject.primarysdgSDG-9: Industry, innovation and infrastructure
dc.subject.secondarysdgSDG-4: Quality education
dc.titleMarkov chain monte carlo methods vs. variational inference approaches in posterior density estimation for bayesian neural networks
dc.typeDissertation

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