Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

Oxygen depletion in the western Baltic Sea is not uncommon. Oxygen-poor conditions regularly occur in deeper waters, placing ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

A study on high-concurrency payment systems proposes a distributed architecture with layered consistency control to ...

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. Inverse protein folding is a critical ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...

A new study led by researchers at The University of New Mexico School of Medicine analyzed electronic health records for more than 1.3 million patients served by the Veterans Health Administration ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

Samuel Kaski’s two-part research lab in ELLIS Institute Finland (Probabilistic Machine Learning, Aalto University) and the Centre for AI Fundamentals in University of Manchester, is searching for ...