Browsing Electronic Systems Engineering (ESE) by Subject "Physics Informed Machine Learning"
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Physics-Informed Neural Network-Based Solution for the Poisson-Boltzmann Equation in an Independent Double-Gate MOSFET
Physics-Informed Neural Networks (PINNs) have emerged as a promising framework for solving partial differential equations (PDEs) by incorporating physical constraints into deep learning models. However, their convergence ...