Science

Researchers have developed a rigorous benchmark to evaluate how well artificial intelligence can forecast outcomes and generate profits in live, decentralized prediction markets.

Researchers are harnessing the power of artificial intelligence to forecast the development of post-traumatic epilepsy using standard clinical notes, offering a potential alternative to reliance on expensive and time-consuming brain imaging.

New research reveals a surprising connection between machine learning, database systems, and formal logic by framing algorithms as transformations within a structured mathematical framework.

A new Bayesian approach provides a principled way to identify unusual nodes within graph-structured data, accounting for inherent uncertainty.

A new deep learning framework combines longitudinal MRI scans with large language models to forecast patient outcomes and provide clearer, more interpretable insights.

A new analysis reveals how media coverage of catastrophic and violent events evolves over time, moving beyond initial reporting to focus on recovery and underlying ideologies.

A new framework leverages asynchronous learning and probability aggregation to improve disaster detection using data from diverse, unconnected devices.

A new graph neural network model leverages dual-path filtering to identify deceptive patterns in complex financial transactions.

New research shows artificial intelligence can dramatically improve the speed and accuracy of interpreting critical communications from ships in distress.

New research suggests large language models can effectively identify methodological flaws in machine learning studies, offering a path toward more reliable AI research.