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 181–190 of 703 papers

Title	Date	Tasks	Status	Score
Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study	Feb 11, 2024	Anomaly DetectionBenchmarking	CodeCode Available	5
Efficient Curation of Invertebrate Image Datasets Using Feature Embeddings and Automatic Size Comparison	Dec 20, 2024	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
Anomaly Detection in Networks via Score-Based Generative Models	Jun 27, 2023	Anomaly DetectionOutlier Detection	CodeCode Available	5
D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments	Oct 15, 2022	ClusteringOutlier Detection	CodeCode Available	5
Dimensionality-Aware Outlier Detection: Theoretical and Experimental Analysis	Jan 10, 2024	Outlier Detection	CodeCode Available	5
Data-driven modeling of time-domain induced polarization	Jul 30, 2021	DenoisingGeophysics	CodeCode Available	5
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III	Jul 19, 2019	BIG-bench Machine LearningLength-of-Stay prediction	CodeCode Available	5
Distribution and volume based scoring for Isolation Forests	Sep 20, 2023	Outlier Detection	CodeCode Available	5
Do Ensembling and Meta-Learning Improve Outlier Detection in Randomized Controlled Trials?	Nov 9, 2023	Meta-LearningModel Selection	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