Physics-guided machine learning reveals I-V characteristics in GaN CAVET, suggesting improved modeling techniques.
This paper presents a physics-guided machine learning (PGML) approach to model the I-V characteristics of GaN current aperture vertical field effect transistors (CAVET). By adopting the method of transfer learning and the shortcut structure, a physically guided neural network model is established. The shallow neural network with <!-- MathType@Translator@5@5@MathML2 (no namespace).tdl@MathML 2.0 (no namespace)@ -->
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Wu et al. (2025) studied this question.
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