Algorithm generates plausible extreme-event scenarios without extreme-event training data

KEY POINTS

1. Researchers describe a new algorithm that can generate and anticipate unprecedented extreme-event scenarios for systems like critical infrastructure and global supply chains, while operating without requiring historical extreme-event training data.
2. The approach aims to produce plausible, high-impact scenarios even when examples of such extremes are scarce or absent in the data.
3. If validated and robust, this method could improve preparedness and risk assessment by producing plausible extreme scenarios even when historical extreme data are lacking.