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 291–300 of 703 papers

Title	Date	Tasks	Status
On Language Clustering: A Non-parametric Statistical Approach	Sep 14, 2022	ClusteringOutlier Detection	—Unverified
Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data	Aug 30, 2022	Anomaly DetectionOutlier Detection	—Unverified
Shaken, and Stirred: Long-Range Dependencies Enable Robust Outlier Detection with PixelCNN++	Aug 29, 2022	Outlier Detection	CodeCode Available
Detecting Surprising Situations in Event Data	Aug 29, 2022	Outlier Detection	—Unverified
Hyperparameter Optimization for Unsupervised Outlier Detection	Aug 24, 2022	Hyperparameter OptimizationMeta-Learning	—Unverified
Semantic Driven Energy based Out-of-Distribution Detection	Aug 23, 2022	object-detectionObject Detection	—Unverified
Outlier Detection using Self-Organizing Maps for Automated Blood Cell Analysis	Aug 18, 2022	Outlier DetectionOut-of-Distribution Detection	—Unverified
A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images	Aug 16, 2022	Image RegistrationOutlier Detection	—Unverified
Enhancement to Training of Bidirectional GAN : An Approach to Demystify Tax Fraud	Aug 16, 2022	Outlier Detection	—Unverified
SSDBCODI: Semi-Supervised Density-Based Clustering with Outliers Detection Integrated	Aug 10, 2022	ClusteringOutlier 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