most citedNeural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures

34 citations · 40 across the 3 of their papers we have counts for

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cs.CE2023★ 6 cited

Graph Neural Networks for Aerodynamic Flow Reconstruction from Sparse Sensing

Gregory Duthé, Imad Abdallah, Sarah Barber +1

Sensing the fluid flow around an arbitrary geometry entails extrapolating from the physical quantities perceived at its surface in order to reconstruct the features of the surround…