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20222026
most citedComputational Fluid Dynamics and Machine Learning as tools for Optimization of Micromixers geometry

1 citations · 1 across the 4 of their papers we have counts for

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cs.LG2026

Adaptive Quantum Physics-Informed Neural Networks for Differential Equations with Applications to Fluid Dynamics

Fabio Pereira dos Santos, Renato Portugal, Júlio de Castro Vargas Fernandes +1

Physics-informed neural networks (PINNs) have emerged as a versatile approach for solving nonlinear partial differential equations (PDEs), yet achieving high accuracy efficiently u…