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approximation theory can be automated by a (neural network) guided search over the action space of standard tools (e.g., Hölder inequalities, Sobolev embeddings, ...). Certain proofs in these fields require
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project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
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project funded by the Waterloo Foundation , exploring the neural mechanisms of balance control in children with and without Developmental Coordination Disorder (DCD). This is a hands-on role that will
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project funded by the Waterloo Foundation , exploring the neural mechanisms of balance control in children with and without Developmental Coordination Disorder (DCD). This is a hands-on role that will
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developing adaptive numerical schemes powered by advanced nonlinear approximations—like Gaussian mixtures and neural networks. The key challenge? Designing robust and stable numerical schemes that remain