Researchers have developed a novel artificial intelligence framework that combines geometric and stochastic modeling of physiological data to improve prediction of life-threatening events like SUDEP and stroke.
Researchers are leveraging the power of large language models to generate realistic, data-driven stress tests for financial portfolios.
A new methodology leverages high-performance computing to comprehensively assess power grid vulnerability to cascading failures and identify critical infrastructure.
A new methodology moves beyond qualitative assessments to model cybersecurity risks amplified by artificial intelligence.
A new pipeline leverages the efficiency of small language models alongside traditional tree ensembles to accurately predict injury severity from city-wide crash data.
Researchers have developed a structured methodology for quantifying the potential harms of increasingly powerful artificial intelligence systems.
A novel approach combines the power of deep learning with established stochastic modeling to achieve more accurate asset price predictions.
As artificial intelligence systems become more powerful, a proactive and rigorous approach to risk assessment is crucial for safe and responsible development.
New research demonstrates that major Japanese bank mergers trigger positive market responses and sustained benefits for other institutions within the sector.
A new data-driven approach leverages graph neural networks to guarantee the stability of large-scale interconnected systems, even with unknown underlying dynamics.