Abstract: In this study, physics-informed graph residual learning (PhiGRL) is proposed as an effective and robust deep learning (DL)-based approach for 3-D electromagnetic (EM) modeling. Extended from ...
Abstract: In the field of operator equations, solving the inner inverses is essential. In this paper, based on the Lagrangian function a class of block Gauss-Seidel methods is proposed, which contains ...
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