Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures. Metal nanoparticles catalyze reactions ...

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...

The National Academies of Sciences, Engineering, and Medicine are private, nonprofit institutions that provide expert advice on some of the most pressing challenges facing the nation and world. Our ...

RIT computer science professor Weijie Zhao has earned a National Science Foundation CAREER Award to defend machine learning ...

The course emphasizes interpretable machine learning techniques and their applications in the financial services industry. Students will develop machine learning models, explain model predictions, and ...

Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...

Researchers have published research detailing their development of an AI framework to detect defects in additively ...

With the growing emphasis on sustainable development, the demand for environmentally friendly solvents in green chemical ...