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 ...

What began with a focus on weather forecasting has evolved toward addressing errors in scientific modeling. In the collaborative environment of the Penn State Institute for Computational and Data ...

see environment file for full list of prerequisites. Tutorial implementations use Tensorflow > 2.0 (Keras) or Pytorch, but versions for Tensorflow 1.x users based on the deprecated tf.contrib module ...

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