In my latest Signal Spot, I had my Villanova students explore machine learning techniques to see if we could accurately ...

A new study by Justin Grandinetti of the University of North Carolina at Charlotte challenges one of the most dominant narratives in artificial intelligence: that modern AI systems are inherently ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular simulations for unprecedented lengths of time, even at temperatures as high as ...

Built on a new architecture KumoRFM-2 achieves state-of-the-art results across 41 predictive tasks and four major benchmarks, ...

Analysis of the 191 samples shows that 55 percent of groundwater falls within low to no restriction categories for irrigation ...

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale.

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale. By integrating daily ...

Yanran Li's AI-driven Marketing Mix Modeling (MMM) framework revolutionizes enterprise resource allocation by integrating ...

New research reveals a model to predict chronic immune thrombocytopenia in children at diagnosis. Learn how it could guide ...

The cryptocurrency market has been one of the most data-heavy financial sectors, with daily trading volumes reaching over ...