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 201–210 of 703 papers

Title	Date	Tasks	Status	Score
Do Ensembling and Meta-Learning Improve Outlier Detection in Randomized Controlled Trials?	Nov 9, 2023	Meta-LearningModel Selection	CodeCode Available	5
D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments	Oct 15, 2022	ClusteringOutlier Detection	CodeCode Available	5
Distribution and volume based scoring for Isolation Forests	Sep 20, 2023	Outlier Detection	CodeCode Available	5
A geometric perspective on functional outlier detection	Sep 14, 2021	Outlier Detection	CodeCode Available	5
Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers	May 30, 2025	Outlier Detection	CodeCode Available	5
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training	Jun 16, 2021	Intent DetectionOutlier Detection	CodeCode Available	5
Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly Detection	Feb 8, 2018	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	5
Adversarial Subspace Generation for Outlier Detection in High-Dimensional Data	Apr 10, 2025	feature selectionOne-Class Classification	CodeCode Available	5
Depth-Based Object Tracking Using a Robust Gaussian Filter	Feb 19, 2016	Computational EfficiencyObject	CodeCode Available	5
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis	Feb 11, 2023	Image-text RetrievalKnowledge Graphs	CodeCode Available	5

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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