The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Understanding and preventing drug side effects holds a profound influence on drug development and utilization, profoundly impacting patients’ physical and mental well-being. Traditional artificial ...