most citedReconstructing velocity and pressure from sparse noisy particle tracks using Physics-Informed Neural Networks

59 citations · 59 across the 1 of their papers we have counts for

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1 paper

physics.flu-dyn2022★ 59 cited

Reconstructing velocity and pressure from sparse noisy particle tracks using Physics-Informed Neural Networks

Patricio Clark Di Leoni, Karuna Agarwal, Tamer Zaki +2

Volume-resolving imaging techniques are rapidly advancing progress in experimental fluid mechanics. However, reconstructing the full and structured Eulerian velocity and pressure f…