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

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

So much of our health is invisible even to ourselves, and one of the biggest barriers to better health is simply not knowing what's going on,' says Apple’s Steve Waydo, director for health sensing.

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 ...

To his credit, Kasy is a realist here. He doesn’t presume that any of these proposals will be easy to implement. Or that it will happen overnight, or even in the near future. The troubling question at ...

Learn how AI-driven personalization transforms customer loyalty. Explore predictive modeling and data strategies for ...

Competition law has long treated communication between competitors as the lifeblood of collusion. The more transparent rivals become about pricing intentions, the greater the risk of coordinated ...

Muons tend to scatter more from high-atomic-number materials, so the technique is particularly sensitive to the presence of materials such as uranium. As a result, it has been used to create systems ...