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clinical trials to assess its ability to measure hydration state. This project would use data from WearOptimo’s hydration sensor and develop novel Bayesian methods to model hydration state. How can hydration
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structures, Bayesian approaches are proposed along with the supersaturated and D-optimal designs in the literature. This project aims to explore the current literature on Bayesian supersaturated D-optimal
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The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
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In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
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plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
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Advanced strongly typed languages like Haskell and emerging type systems like refinement types (as implemented in Liquid Haskell) offer strong guarantees about the correctness of programs. However, when type errors occur it can be difficult for programmers to understand their cause. Such...
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motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise
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nodes and chemical bonds as edges. Analysis these networks are important as they may provide AI-based approaches for drug discovery. This project will focus on representing and inferring chemical or
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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polycrystalline material during plastic deformation in order to eventually predict the manner in which materials deform and fail. As a first step, we wish to infer a distribution of the directions of deformation