ADBench: Anomaly Detection Benchmark

Benchmarking Node Outlier Detection on Graphs

ELECT: Toward Unsupervised Outlier Model Selection

ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions

Automatic Unsupervised Outlier Model Selection

Revisiting Time Series Outlier Detection: Definitions and Benchmarks

SUOD: Accelerating Large-scale Unsupervised Heterogeneous Outlier Detection

Outlier detection (OD) is a key data mining task for identifying abnormal objects from general samples with numerous high-stake applications including fraud detection and intrusion detection. Due to the lack of ground truth labels, practitioners …

TODS: An Automated Time Series Outlier Detection System

A Data Denoising Approach to Optimize Functional Clustering of Single Cell RNA-sequencing Data

AutoAudit: Mining Accounting and Time-Evolving Graphs