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 21–30 of 703 papers

Title	Date	Tasks	Status	Hype
Non-parametric online market regime detection and regime clustering for multidimensional and path-dependent data structures	Jun 27, 2023	ClusteringOutlier Detection	CodeCode Available	1
Energy-based Detection of Adverse Weather Effects in LiDAR Data	May 25, 2023	Autonomous VehiclesOutlier Detection	CodeCode Available	1
Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense	Mar 23, 2023	Language ModellingOutlier Detection	CodeCode Available	1
Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning	Mar 21, 2023	Outlier Detection	CodeCode Available	1
SplitOut: Out-of-the-Box Training-Hijacking Detection in Split Learning via Outlier Detection	Feb 16, 2023	Outlier Detection	CodeCode Available	1
Open-Set Likelihood Maximization for Few-Shot Learning	Jan 20, 2023	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
RbA: Segmenting Unknown Regions Rejected by All	Nov 25, 2022	AllAnomaly Detection	CodeCode Available	1
PNI : Industrial Anomaly Detection using Position and Neighborhood Information	Nov 22, 2022	Anomaly DetectionOutlier Detection	CodeCode Available	1
OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming language	Nov 8, 2022	Outlier Detection	CodeCode Available	1
Toward Unsupervised Outlier Model Selection	Nov 3, 2022	Meta-Learningmodel	CodeCode Available	1

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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