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 121–130 of 703 papers

Title	Date	Tasks	Status	Score
A Method of Moments Embedding Constraint and its Application to Semi-Supervised Learning	Apr 27, 2024	image-classificationImage Classification	CodeCode Available	5
A Radiometric Correction based Optical Modeling Approach to Removing Reflection Noise in TLS Point Clouds of Urban Scenes	Jul 3, 2024	3D ReconstructionAutonomous Driving	CodeCode Available	5
D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments	Oct 15, 2022	ClusteringOutlier Detection	CodeCode Available	5
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos	Mar 8, 2019	Anomaly DetectionDecoder	CodeCode Available	5
Embedding-Based Complex Feature Value Coupling Learning for Detecting Outliers in Non-IID Categorical Data	Jul 1, 2019	Outlier Detection	CodeCode Available	5
Learning to Classify Open Intent via Soft Labeling and Manifold Mixup	Apr 16, 2022	intent-classificationIntent Classification	CodeCode Available	5
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis	Feb 11, 2023	Image-text RetrievalKnowledge Graphs	CodeCode Available	5
Dimensionality-Aware Outlier Detection: Theoretical and Experimental Analysis	Jan 10, 2024	Outlier Detection	CodeCode Available	5
Depth-Based Object Tracking Using a Robust Gaussian Filter	Feb 19, 2016	Computational EfficiencyObject	CodeCode Available	5
Dense open-set recognition with synthetic outliers generated by Real NVP	Nov 22, 2020	Autonomous Drivingimage-classification	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