have developed a new machine learning model to predict the dielectric function of materials, rather than calculating from first-principles. The dielectric function measures the polarization of ...

Abstract: Machine ... parameters are model parameters and configurable such as weights of neural networks and their estimation can be done using data set. The hyperparameters such as learning rate, ...

This article presents a machine learning ... reducing the size of the training data needed to obtain an accurate ML model. ML-based feedforward power flow control can achieve comparable accuracy as ...