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 31–40 of 703 papers

Title	Date	Tasks	Status	Hype
Unsupervised Graph Outlier Detection: Problem Revisit, New Insight, and Superior Method	Oct 24, 2022	AttributeGraph Outlier Detection	CodeCode Available	1
Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization	Sep 26, 2022	Outlier DetectionOut-of-Distribution Detection	CodeCode Available	1
ECO-TR: Efficient Correspondences Finding Via Coarse-to-Fine Refinement	Sep 25, 2022	Outlier Detection	CodeCode Available	1
FaceMap: Towards Unsupervised Face Clustering via Map Equation	Mar 21, 2022	ClusteringCommunity Detection	CodeCode Available	1
NEAR - Newborns EEG Artifact Removal	Jan 15, 2022	EEGEEG Artifact Removal	CodeCode Available	1
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions	Jan 2, 2022	Anomaly DetectionOutlier Detection	CodeCode Available	1
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks	Dec 10, 2021	Anomaly DetectionGraph Neural Network	CodeCode Available	1
OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization	Dec 1, 2021	Novelty DetectionOutlier Detection	CodeCode Available	1
TOD: GPU-accelerated Outlier Detection via Tensor Operations	Oct 26, 2021	CPUFraud Detection	CodeCode Available	1
Generalized Out-of-Distribution Detection: A Survey	Oct 21, 2021	Anomaly DetectionAutonomous Driving	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