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 411–420 of 703 papers

Title	Date	Tasks	Status
Measuring Dependence with Matrix-based Entropy Functional	Jan 25, 2021	BIG-bench Machine LearningOutlier Detection	CodeCode Available
Dense outlier detection and open-set recognition based on training with noisy negative images	Jan 22, 2021	Open Set LearningOutlier Detection	—Unverified
An Empirical Exploration of Open-Set Recognition via Lightweight Statistical Pipelines	Jan 1, 2021	open-set classificationOpen Set Learning	—Unverified
Outlier Preserving Distribution Mapping Autoencoders	Jan 1, 2021	Outlier Detection	—Unverified
Enhancing Visual Representations for Efficient Object Recognition during Online Distillation	Jan 1, 2021	Object RecognitionOutlier Detection	—Unverified
Outlier Robust Optimal Transport	Jan 1, 2021	Outlier Detection	—Unverified
Identifying Informative Latent Variables Learned by GIN via Mutual Information	Jan 1, 2021	Adversarial AttackDisentanglement	—Unverified
Suppressing Outlier Reconstruction in Autoencoders for Out-of-Distribution Detection	Jan 1, 2021	Outlier DetectionOut-of-Distribution Detection	—Unverified
Probabilistic Outlier Detection and Generation	Dec 22, 2020	Outlier Detection	—Unverified
Incremental Data-driven Optimization of Complex Systems in Nonstationary Environments	Dec 14, 2020	Ensemble LearningOutlier 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