Containing Financial Contagion: A Control-Theoretic Approach
New research demonstrates how optimal control techniques can be used to model and mitigate the spread of distress within complex financial networks.
New research demonstrates how optimal control techniques can be used to model and mitigate the spread of distress within complex financial networks.

Researchers have developed a novel model that understands financial transactions by treating them as natural language, unlocking insights from limited data.

Researchers have developed a new AI framework that leverages natural language understanding to improve the accuracy and interpretability of traffic forecasting, especially during unexpected events.

A new framework efficiently integrates personal and market data to deliver more relevant and personalized financial asset recommendations using large language models.

New research demonstrates how explainable AI is unlocking the ‘black box’ of wildfire prediction models to build greater trust in forecasts and improve disaster preparedness.

A new multi-agent system leverages large language models to forecast hazards and enhance safety protocols in complex operational settings.

A new approach to combining weather model predictions significantly boosts the accuracy of forecasting high-impact events, offering crucial improvements for disaster preparedness.

A new approach leverages artificial intelligence and localized data to create adaptable regional boundaries that better address specific disaster risks and enable more targeted interventions.

New research reveals that the impact of data quality on credit risk models isn’t always what you’d expect.
A new analysis reveals that surprisingly few manipulated data points can compromise the accuracy and reliability of artificial intelligence systems used in medical diagnosis and treatment.