Outlier Detection

Outlier Detection is a task of identifying a subset of a given data set which are considered anomalous in that they are unusual from other instances. It is one of the core data mining tasks and is central to many applications. In the security field, it can be used to identify potentially threatening users, in the manufacturing field it can be used to identify parts that are likely to fail.

Source: Coverage-based Outlier Explanation

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1–10 of 703 papers

Title	Date	Tasks	Status	Hype
ADBench: Anomaly Detection Benchmark	Jun 19, 2022	Anomaly DetectionOutlier Detection	CodeCode Available	3
DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning	Jun 7, 2022	AutoMLBIG-bench Machine Learning	CodeCode Available	3
Interactive Continual Learning: Fast and Slow Thinking	Mar 5, 2024	Continual LearningOutlier Detection	CodeCode Available	2
Towards Total Recall in Industrial Anomaly Detection	Jun 15, 2021	3D Anomaly DetectionAnomaly Classification	CodeCode Available	2
TODS: An Automated Time Series Outlier Detection System	Sep 18, 2020	Outlier DetectionTime Series	CodeCode Available	2
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection	Jul 1, 2016	Anomaly DetectionDecoder	CodeCode Available	2
Out-of-Distribution Detection on Graphs: A Survey	Feb 12, 2025	Anomaly DetectionGraph Anomaly Detection	CodeCode Available	1
Fuzzy Granule Density-Based Outlier Detection with Multi-Scale Granular Balls	Jan 6, 2025	Outlier Detection	CodeCode Available	1
Coniferest: a complete active anomaly detection framework	Oct 22, 2024	Anomaly DetectionOutlier Detection	CodeCode Available	1
STAMP: Outlier-Aware Test-Time Adaptation with Stable Memory Replay	Jul 22, 2024	Outlier DetectionTest-time Adaptation	CodeCode Available	1

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All datasets ECG5000 Balance scale_class 1 Breast cancer Wisconsin_class 2 Breast cancer Wisconsin_class 4 Fashion-MNIST Glass identification Heart-C Hepatitis Internet Ad Ionosphere_class b SKAB

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	VRAE+SVM	Accuracy	0.98	—	Unverified
2	F-t ALSTM-FCN	Accuracy	0.95	—	Unverified
3	GENDIS	Accuracy	0.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	99.03	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	37.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	65.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PAE	AUROC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	99.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC	0.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC-ROC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC-ROC	0.93	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	86.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSTMCaps	Average F1	0.74	—	Unverified