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 ...

But even these behemoths, like all machine learning models, are just functions at heart — mathematical shapes. In the right context, they can be extremely powerful tools, but they also have familiar ...

Scientists have developed a new model for heat exchangers of heat pumps, combining strengths of numerical modeling and ...

Abstract: This paper proposes a model based on a machine learning algorithm, extreme learning machine (ELM), and the pole-residue-based transfer function (TF) for parametric modeling of ...

Machine learning depends on a number of algorithms for turning a data set into a model. Which algorithm ... activation functions. In a feed-forward network, the neurons are organized into distinct ...

The result is a machine learning framework that is easier to work with—for example, by using the relatively simple Keras API for model training ... the output of one function to the input ...

The illustration depicts some of the innovative ideas that underpin the new machine learning model that can quickly and accurately predict the dielectric function of simple molecules, such as ...