Science

Researchers have developed a novel machine learning method that leverages network structure to more accurately predict how robust complex systems are to disruptions.

A new data-driven approach reveals how distant weather patterns shape regional rainfall and improve our understanding of climate variability.

New research leverages machine learning to understand the complex factors influencing how and when people flee approaching wildfires.

New research highlights how detailed weather and property data can dramatically improve the accuracy of flood risk modeling and insurance pricing.

New research shows how volatility estimates derived from local food price data can serve as an early warning system for economic instability in developing nations.

As AI systems gain autonomy, a robust security framework is crucial, and this review lays the groundwork for formally verifying their trustworthiness.

A new approach to modeling financial return dynamics leverages the full distribution of potential outcomes, offering more accurate predictions of extreme losses.

Researchers have developed a novel method that enhances both the accuracy and interpretability of time-series predictions, offering significant improvements for applications like early warning systems and predictive maintenance.

A new approach to causal learning argues that integrating human expertise and AI can overcome limitations of purely data-driven methods.

A new framework combines the strengths of machine learning and symbolic reasoning to more accurately forecast how colorectal cancers will respond to treatment.