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to space-related technologies, and implement their solutions as cutting-edge, efficient numerical methods. The focus is on building rigorous frameworks that can capture the complexity of challenging
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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific
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systematically linking experimental and literature-based biological insight with advanced numerical methods, the hope is to provide a toolbox of well-grounded models and design primitives that can be used
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