Sequential Anomaly Detection with Local and Global Explanations (GLEAD)

GLEAD: Sequential Anomaly Detection with Local and Global Explanations

GLEAD is a globally and locally explainable method for sequential anomaly detection. It uses multi-head self-attention and prototypes for normal and abnormal sequences, providing local explanations by highlighting anomalous entries and global explanations by identifying common anomaly patterns across data.