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20222025
most citedPhysics-informed neural networks for learning the homogenized coefficients of multiscale elliptic equations

12 citations · 12 across the 2 of their papers we have counts for

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math-ph2024

Asymptotic-preserving neural networks for the semiconductor Boltzmann equation and its application on inverse problems

Liu Liu, Yating Wang, Xueyu Zhu +1

In this paper, we develop the Asymptotic-Preserving Neural Networks (APNNs) approach to study the forward and inverse problem for the semiconductor Boltzmann equation. The goal of…