15 citations · 18 across the 9 of their papers we have counts for
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cs.LG2023★ 2 cited
INFINITY: Neural Field Modeling for Reynolds-Averaged Navier-Stokes Equations
Louis Serrano, Leon Migus, Yuan Yin +2
For numerical design, the development of efficient and accurate surrogate models is paramount. They allow us to approximate complex physical phenomena, thereby reducing the computa…
cs.LG2023★ 15 cited
Operator Learning with Neural Fields: Tackling PDEs on General Geometries
Louis Serrano, Lise Le Boudec, Armand Kassaï Koupaï +4
Machine learning approaches for solving partial differential equations require learning mappings between function spaces. While convolutional or graph neural networks are constrain…