Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

The varied topography of the Western United States—a patchwork of valleys and mountains, basins and plateaus—results in minutely localized weather. Accordingly, snowfall forecasts for the mountain ...

If program staff suspects you may have used AI tools to complete assignments in ways not explicitly authorized or suspect other violations of the honor code, they will contact you via email. Be sure ...

The field of kidney transplantation is increasingly incorporating machine learning (ML) strategies to enhance the accuracy of survival predictions, thus, transforming patient outcomes in significant ...

Looking ahead, leveraging China Mobile’s AaaS (Ability as a Service) digital capability platform, the project team plans to build a unified, shareable capability framework and replicate China Mobile ...

Cosmic rays are high-energy particles that constantly bombard Earth from space and are influenced by the sun's magnetic activity. When the sun is active, fewer of these particles reach Earth; when the ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Neuromorphic computing systems, encompassing both digital and analog neural accelerators, promise to revolutionize AI ...