Algorithm generates plausible extreme-event scenarios without extreme-event training data
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. The approach aims to produce plausible, high-impact scenarios even when examples of such extremes are scarce or absent in the data.