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Dowe, 1999a) ensures that - at least in principle, given enough search time - MML can infer any underlying computable model in a data-set. A consequence of this is that we can (e.g.) put latent factor
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and 45% worldwide. Predictive models based on Artificial Intelligence (AI) techniques will enable risk stratification to implement personalized medicine for prevention and earlier diagnosis of GDM. One
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Recent advancements in foundation models have significantly improved AI systems' capabilities in autonomous tool usage and complex reasoning. However, their potential for location-based and map
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, human society and our agriculture, that are typical of complex systems. Ecosystem and social system modelling therefore, including simulation, can play a key role to understand food production and
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In this project, we aim to pioneer foundational models specifically designed for time series data—a critical step forward in handling vast and complex temporal datasets generated across domains like
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accepted by the intended users due to their limited capabilities to sustain long-term interactions. In this project we propose to develop compositional vision-language models for social robots, enabling them
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an integrated scalable framework that supports model evaluation, assess the performance and hyper parameter optimisation based on clinical and molecular data cohorts. The project will also intend to adopt
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This project involves model-based depth of anaesthesia monitoring using autoregressive moving average modelling and neural mass and neural field modelling of the electroencephalographic (EEG) signal
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cancers. Working as part of a translational research team, you will support a wide range of laboratory-based activities—spanning tissue banking, sample preparation for molecular analysis, and maintenance
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this work we will use Theory of Mind (ToM) to reason about the mental models of the actors involved in AI systems, designers, agents and users and expand on the "Model Reconciliation Problem" or reconciling