Towards efficient Bayesian inference : Cox processes and probabilistic integration
In this thesis we present a variety of new, continuous, Bayesian Gaussian-process-driven Cox process models. These are used to model sparse event data distributed on a continuous domain, where the events may have a tendency to cluster. These find direct use in application areas ranging from disease...
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University of Oxford
2017
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| Online Access: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.748732 |