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 101–110 of 703 papers

Title	Date	Tasks	Status
Robust Conformal Outlier Detection under Contaminated Reference Data	Feb 7, 2025	Conformal PredictionOutlier Detection	CodeCode Available
CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning	Feb 6, 2025	ImputationOutlier Detection	CodeCode Available
RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples	Jan 28, 2025	DiversityOutlier Detection	CodeCode Available
Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networks	Jan 23, 2025	Beam PredictionOutlier Detection	—Unverified
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model	Jan 20, 2025	Anomaly DetectionOutlier Detection	—Unverified
Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders	Jan 19, 2025	Feature ImportanceImputation	—Unverified
Temporal Analysis of Adversarial Attacks in Federated Learning	Jan 19, 2025	Federated LearningOutlier Detection	—Unverified
Outlyingness Scores with Cluster Catch Digraphs	Jan 9, 2025	Outlier Detection	—Unverified
On the Adversarial Robustness of Benjamini Hochberg	Jan 6, 2025	Adversarial RobustnessAnomaly Detection	—Unverified
An Efficient Outlier Detection Algorithm for Data Streaming	Jan 2, 2025	Anomaly DetectionFraud Detection	—Unverified

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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