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Physics and Number Theory. More broadly, the School also has research strengths in Bayesian and Monte Carlo Methods, Biomathematics, Biostatistics and Ecology, Computational Mathematics, Data Science
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interests in the areas of applied and pure mathematics, and statistics. In Statistics, the School has research strengths in Bayesian and Monte Carlo Methods, Biostatistics and Ecology, Combinatorics, Data
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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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, Joshua W. and D.L. Dowe (2005). ``Minimum Message Length and Generalized Bayesian Nets with Asymmetric Languages'', Chapter 11 (pp265-294) in P. Gru:nwald, I. J. Myung and M. A. Pitt (eds.), Advances in
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numbers of minimally-interpretable models being used, as opposed to traditional models like decision trees, or even Bayesian and statistical machine learning models. Explanations of models are also needed
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networks, Bayesian inference, computational neuroscience, mathematics.
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Processing/Control Path Planning/Trajectory Planning Multi-Target Tracking/Multi-Object Tracking, Bayesian Filtering, Radom Finite Set filters or closely related multi-target tracking approaches in radar
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the Faculty of Science. We will apply Bayesian approaches such as the information-theoretic minimum message length (MML) principle and other approaches to develop a path towards statistically-optimal algorithms
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for the prediction task, such as predicting the bioassay of a given chemical network. One of the approaches that will be considered will be the Bayesian information-theoretic Minimum Message Length (MML) principle
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back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum message length (MML) approach (Wallace and Boulton, 1968