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 521–530 of 703 papers

Title	Date	Tasks	Status
NeuronInspect: Detecting Backdoors in Neural Networks via Output Explanations	Nov 18, 2019	Backdoor AttackOutlier Detection	—Unverified
News-based Business Sentiment and its Properties as an Economic Index	Oct 20, 2021	ArticlesOutlier Detection	—Unverified
Noisy Subspace Clustering via Thresholding	May 15, 2013	ClusteringOutlier Detection	—Unverified
Nonconvex Approach for Sparse and Low-Rank Constrained Models with Dual Momentum	Jun 6, 2019	ClusteringDenoising	—Unverified
Non-parametric cumulants approach for outlier detection of multivariate financial data	May 18, 2023	Outlier Detection	—Unverified
Oaken: Fast and Efficient LLM Serving with Online-Offline Hybrid KV Cache Quantization	Mar 24, 2025	GPULarge Language Model	—Unverified
Ocean Data Quality Assessment through Outlier Detection-enhanced Active Learning	Dec 17, 2023	Active LearningOutlier Detection	—Unverified
ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches	Nov 20, 2023	Depth EstimationDimensionality Reduction	—Unverified
One-Class Kernel Spectral Regression	Jul 3, 2018	Graph EmbeddingOne-class classifier	—Unverified
One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities	Apr 17, 2023	Anomaly DetectionLesion Detection	—Unverified

Show:10 25 50

← PrevPage 53 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