Science

A new deep learning approach effectively combines diverse financial opinions to improve sentiment analysis and potentially predict market trends.

A new framework leverages Bayesian neural networks to monitor the real-time condition of structures with unprecedented accuracy and reliability.

As AI systems gain the ability to act independently, ensuring their ethical and safe operation requires a new approach to risk management and control.

Researchers have developed a scalable method to build comprehensive firm-to-firm production networks from publicly available data, offering unprecedented insight into economic dependencies.

A new approach combines satellite imagery, road network details, and accident history to significantly improve the prediction of traffic accidents and identify key contributing factors.

Researchers have developed a novel framework to detect and mitigate a critical vulnerability – atomicity violations – within the code that powers decentralized applications.

A new approach to graph neural networks explicitly quantifies prediction uncertainty, enhancing robustness in challenging data scenarios.

As data science projects become increasingly complex, traditional risk management approaches fall short, overlooking critical ethical and societal considerations.

A new framework, GraphMatch, combines the power of natural language processing with graph neural networks to significantly improve recommendations in fast-moving, two-sided digital marketplaces.

A novel framework uses artificial intelligence to reconcile on-chain data with issuer reports, providing a more comprehensive view of stablecoin credibility.