When it comes to predicting disasters brought on by extreme events (think earthquakes, pandemics or "rogue waves" that could destroy coastal structures),
Researchers from Brown and MIT suggest how scientists can circumvent the need for massive data sets to forecast extreme events with the combination of an advanced machine learning system and sequential sampling techniques.