Data-driven Modelling and Scientific Machine Learning in Continuum Physics

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Physics-based Machine Learning and Data-driven Reduced-order Modeling

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This thesis considers the task of learning efficient low-dimensional models for dynamical systems. To be effective in an engineering setting, these models must

Data-Driven Fluid Mechanics

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Data-driven methods have become an essential part of the methodological portfolio of fluid dynamicists, motivating students and practitioners to gather practica

Tensor Voting

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Introduction -- Tensor voting -- Stereo vision from a perceptual organization perspective -- Tensor voting in ND -- Dimensionality estimation manifold learning

Data-driven modeling and optimization in fluid dynamics: From physics-based to machine learning approaches

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