Adaptive Machine Learning for Rare Event Detection

Develop a machine learning framework specifically designed to detect and characterize rare scientific events across different domains (particle physics, astronomical transients, biological anomalies). The system must handle highly imbalanced datasets, implement advanced anomaly detection algorithms, and provide comprehensive uncertainty quantification. Support transfer learning and few-shot learning techniques.