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: Physics-informed neural networks (PINNs) have recently been utilized to tackle wave equation-based forward and inverse problems. However, they encounter challenges in accurately predicting ...
In the context of the rapid development of computer hardware and the continuous improvement of the artificial intelligence and deep learning theory, aiming at the traditional numerical solution method ...
All executable code is in the notebook swe_instructor_code_retreat.ipynb. To directly open the notebook in Google Colab, click the badge below.
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