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Showing 1 to 1 of 1 for “"physics-informed compressed sensing"”.
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Inverse problems in fluid dynamics for magnetic resonance velocimetry
I formulate a digital twin approach to the reconstruction of velocity fields from noisy and sparse magnetic resonance velocimetry signals. The method learns the most probable fluid dynamics model that fits the data by solving a Bayesian inverse Navier-Stokes boundary value problem. This jointly …