Many modern technological challenges crucially depend on the properties of surfaces and interfaces. This includes the control of charge and energy transfer across electrode/electrolyte interfaces in ...

Machine learning has greatly shaped the landscape of computational biology, with the integration of high-throughput data acquisition and burgeoning computational power leading to the creation of ...

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

Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...

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

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 ...

Machine learning methods have found many successful applications in predicting the response variable. However, many machine ...

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 ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

Across Africa, a new generation of policy oriented technologists is beginning to redefine the relationship between governance, economic development, clean energy transition, and Artificial ...