DISYRE: Diffusion-Inspired Synthetic Restoration for Unsupervised Anomaly Detection
Diffusion-Inspired Synthetic Restoration (DISYRE) improves Unsupervised Anomaly Detection in medical images by replacing Gaussian noise with synthetic anomalies.
DTOR: Decision Tree Outlier Regressor for Anomaly Detection in Banking Sector
Decision Tree Outlier Regressor (DTOR) provides rule-based explanations for anomalies, enhancing interpretability in anomaly detection models.
DISYRE: Diffusion-Inspired Synthetic Restoration for Unsupervised Anomaly Detection
Diffusion models are adapted for unsupervised anomaly detection in medical images through synthetic anomaly corruption, leading to improved performance.
DTOR: Decision Tree Outlier Regressor for Anomaly Explanation
Explaining outliers occurrence is crucial in various domains, and the Decision Tree Outlier Regressor (DTOR) provides rule-based explanations for individual data points by estimating anomaly scores.
Privacy Preserving Anomaly Detection on Homomorphic Encrypted Data from IoT Sensors
Homomorphic encryption enables privacy-preserving anomaly detection on IoT data without decryption.
