Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

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

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...

Metals are made of randomly oriented crystals at the microscopic-length scale. The alignment of the crystal faces creates an infinite number of configurations and complex patterns, making simulations ...

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...

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

ZHEJIANG, ZHEJIANG, CHINA, January 21, 2026 /EINPresswire.com/ -- As the global industrial landscape moves further into ...

A brisk theatrical thriller, “Data” perfectly captures the slick, grandiose language with which tech titans justify their potentially totalitarian projects.

Penn Engineers have developed a system that lets robots see around corners using radio waves processed by AI, a capability ...

Cristani, C. and Tessera, D. (2026) A Foundational Protocol for Reproducible Visualization in Multivariate Quantum Data. Open Access Library Journal, 13, 1-13. doi: 10.4236/oalib.1114704 .