Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...

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 ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

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

Finely dispersed particulate matter with a diameter of ≤2.5 μm (PM2.5) poses a significant health- and climate-risk, yet ...

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...

Abstract: Machine learning algorithms and artificial intelligence (AI) have driven a revolution in many scientific and engineering fields. Now, they are slowly making their way into the field of ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Plasma mirrors capable of withstanding the intensity of powerful lasers are being designed through an emerging machine learning framework. Researchers in Physics and Computer Science at the University ...

1 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China 2 State Key Laboratory of Mountain Bridge and Tunnel Engineering, ...

Background and objective: The increasing global prevalence of diabetes has led to a surge in complications, significantly burdening healthcare systems and affecting patient quality of life. Early ...