A research team used flowering data from 169 rice genotypes—each with over 700,000 SNP markers—across multiple environments ...

MIT researchers designed a computationally efficient algorithm for machine learning with symmetric data that also requires fewer data for training than conventional approaches. Their work could inform ...

One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend ...

Wastewater treatment plants (WWTPs) are inherently complex, with nonlinear processes that are challenging to analyze and ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

A machine learning model developed to predict 5-year survival in stage III colorectal cancer patients highlights key ...

Compared with the secondaries market’s largely bottom-up approach to pricing portfolios, Oliver Gottschalg, professor of ...

Machine learning accelerates catalyst discovery by combining theory, AI, and experiments to identify efficient materials for sustainable energy applications.

Researchers in China used machine learning to create diagnostic and prognostic models to aid in identifying idiopathic ...