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Algorithms and modelling for large-scale Bayesian data analysis

Abstract:

Bayesian statistics has emerged as a leading paradigm for the analysis of complicated datasets and for reasoning and making predictions under uncertainty. However, the framework faces significant difficulties when it is applied at scale. As datasets grow larger, simulation-based approaches to inference become unviably expensive. As models become more complex, the naïve application of traditional inference methods does not always produce valid predictions. And as Bayesian methods are applie...

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Division:
MPLS
Department:
Engineering Science
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Author

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Funding agency for:
Cornish, JRM
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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