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 371–380 of 703 papers

Title	Date	Tasks	Status
A geometric perspective on functional outlier detection	Sep 14, 2021	Outlier Detection	CodeCode Available
Cascade Watchdog: A Multi-tiered Adversarial Guard for Outlier Detection	Aug 20, 2021	Outlier DetectionOut-of-Distribution Detection	—Unverified
Robust outlier detection by de-biasing VAE likelihoods	Aug 19, 2021	DecoderOutlier Detection	—Unverified
Out-of-Distribution Detection Using Outlier Detection Methods	Aug 18, 2021	Outlier DetectionOut-of-Distribution Detection	CodeCode Available
Discovering outliers in the Mars Express thermal power consumption patterns	Aug 4, 2021	Outlier Detection	—Unverified
IPOF: An Extremely and Excitingly Simple Outlier Detection Booster via Infinite Propagation	Aug 1, 2021	Outlier Detection	—Unverified
Data-driven modeling of time-domain induced polarization	Jul 30, 2021	DenoisingGeophysics	CodeCode Available
Unsupervised Outlier Detection using Memory and Contrastive Learning	Jul 27, 2021	Contrastive LearningOutlier Detection	—Unverified
Meta-Learning for Relative Density-Ratio Estimation	Jul 2, 2021	Density Ratio EstimationMeta-Learning	—Unverified
Closed-Form, Provable, and Robust PCA via Leverage Statistics and Innovation Search	Jun 23, 2021	ClusteringForm	—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