machine learning

The Yakimovich group "Machine Learning for Infection and Disease" aims to understand the complex network of molecular interactions that is active after the body has been infected with a pathogen.

The use of the new possibilities of machine learning is key here.

In contrast, the author's machine learning algorithm is equipped with atmospheric physics equations that can produce more accurate results faster and with less data.

"Unlike traditional numerical models, our model employs an advanced physics-informed machine learning framework," said author Feng Hu.

In a paper published this week in Physics of Fluids, by AIP Publishing, a pair of researchers from the City University of Hong Kong employed machine learning to more accurately model the boundary layer wind field of tropical cyclones.