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20222026
most citedPhysics-informed PointNet: A deep learning solver for steady-state incompressible flows and thermal fields on multiple sets of irregular geometries

160 citations · 166 across the 8 of their papers we have counts for

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cs.LG2025

Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries

Ali Kashefi, Tapan Mukerji

Kolmogorov-Arnold Networks (KANs) have gained attention as an alternative to traditional multilayer perceptrons (MLPs) for deep learning applications in computational physics, part…

cs.LG2024★ 2 cited

Kolmogorov-Arnold PointNet: Deep learning for prediction of fluid fields on irregular geometries

Ali Kashefi

Kolmogorov-Arnold Networks (KANs) have emerged as a promising alternative to traditional Multilayer Perceptrons (MLPs) in deep learning. KANs have already been integrated into vari…