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 171–180 of 703 papers

Title	Date	Tasks	Status
Deep Learning with Sets and Point Clouds	Nov 14, 2016	ClusteringDeep Learning	—Unverified
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach	May 8, 2025	Conformal PredictionImputation	—Unverified
Detecting abnormal events in video using Narrowed Normality Clusters	Jan 12, 2018	Anomaly DetectionClustering	—Unverified
Symbiotic Hybrid Neural Network Watchdog For Outlier Detection	Feb 28, 2021	Outlier Detection	—Unverified
AI-enabled Blockchain: An Outlier-aware Consensus Protocol for Blockchain-based IoT Networks	Jun 17, 2019	BIG-bench Machine LearningOutlier Detection	—Unverified
Defending Object Detectors against Patch Attacks with Out-of-Distribution Smoothing	May 18, 2022	BIG-bench Machine Learningobject-detection	—Unverified
Contextual Outlier Interpretation	Nov 28, 2017	feature selectionOutlier Detection	—Unverified
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model	Mar 14, 2025	Bayesian InferenceEfficient Exploration	—Unverified
Contextual Unsupervised Outlier Detection in Sequences	Nov 6, 2021	Outlier Detection	—Unverified
Cognitive Deep Machine Can Train Itself	Dec 2, 2016	Outlier 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