New AI Framework SCOT Improves Cross-City Data Transfer for Urban Prediction

Researchers introduced SCOT, a machine learning framework that enables cities with limited labeled data to leverage information from other cities despite different geographic partitions. Using optimal transport theory, SCOT learns explicit correspondences between incompatible region divisions, improving prediction accuracy and stability across multiple cities.