2024
DACR: Distribution-Augmented Contrastive Reconstruction for Time-Series Anomaly Detection
ICASSP 2024accepted
Anomaly detection in time-series data is crucial for identifying faults, failures, threats, and outliers across a range of applications. Recently, deep learning techniques have been applied to this topic, but they often struggle in real-world scenarios that are complex and highly dynamic, e.g., the…