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 321–330 of 703 papers

Title	Date	Tasks	Status
Hierarchical Multiresolution Feature- and Prior-based Graphs for Classification	Jun 3, 2023	ClassificationEdge Detection	—Unverified
Highly Efficient Direct Analytics on Semantic-aware Time Series Data Compression	Mar 17, 2025	Data CompressionOutlier Detection	—Unverified
HLoOP -- Hyperbolic 2-space Local Outlier Probabilities	Dec 6, 2023	Outlier Detection	—Unverified
Holistic Features For Real-Time Crowd Behaviour Anomaly Detection	Jun 16, 2016	Anomaly DetectionBinary Classification	—Unverified
Homophily Outlier Detection in Non-IID Categorical Data	Mar 21, 2021	feature selectionOutlier Detection	—Unverified
Evaluating the Efficacy of Foundational Models: Advancing Benchmarking Practices to Enhance Fine-Tuning Decision-Making	Jun 25, 2024	BenchmarkingDecision Making	—Unverified
Hybridization of Capsule and LSTM Networks for unsupervised anomaly detection on multivariate data	Feb 11, 2022	Anomaly DetectionChange Point Detection	—Unverified
Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles	Jun 15, 2025	Anomaly DetectionAnomaly Forecasting	—Unverified
Hyperbolic Metric Learning for Visual Outlier Detection	Mar 22, 2024	Metric LearningOutlier Detection	—Unverified
A Bayesian Ensemble for Unsupervised Anomaly Detection	Oct 24, 2016	Anomaly DetectionClustering	—Unverified

Show:10 25 50

← PrevPage 33 of 71Next →

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