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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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inference pipelines for soft biomechanical systems, including differentiable physics engines, to support interpretable analysis, parameter estimation, sensitivity studies and uncertainty quantification. By
Searches related to bayesian inference
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