Structural economic models, while parsimonious and interpretable, often exhibit poor data fit and limited forecasting performance. Machine learning models, by contrast, offer substantial flexibility ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Find out how machine learning identifies country-specific health system drivers shaping global cancer survival and highlights ...

By leveraging AI/ML-driven modeling, Keysight enables semiconductor companies to accelerate innovation, reduce development ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

A recent study published in npj Materials Degradation introduces a two-stage machine learning (ML) framework that predicts the degradation of protective coatings under various environmental conditions ...

A team from the Faculty of Medicine and Health Sciences and the Institute of Neurosciences at the University of Barcelona ...

Machine learning researchers using MLX will benefit from speed improvements in macOS Tahoe 26.2, including support for the M5 GPU-based neural accelerators and Thunderbolt 5 clustering. People working ...

A new research paper shows the approach performs significantly better than the random-walk forecasting method.