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 11–20 of 703 papers

Title	Date	Tasks	Status	Hype
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective	May 17, 2024	Backdoor AttackMemorization	CodeCode Available	1
Outlier detection by ensembling uncertainty with negative objectness	Feb 23, 2024	Outlier DetectionPrediction	CodeCode Available	1
Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models	Dec 29, 2023	Data AugmentationDenoising	CodeCode Available	1
FOUND: Foot Optimization with Uncertain Normals for Surface Deformation Using Synthetic Data	Oct 27, 2023	Outlier DetectionSurface Normal Estimation	CodeCode Available	1
MAGIC: Detecting Advanced Persistent Threats via Masked Graph Representation Learning	Oct 15, 2023	Graph Representation LearningOutlier Detection	CodeCode Available	1
LiON: Learning Point-wise Abstaining Penalty for LiDAR Outlier DetectioN Using Diverse Synthetic Data	Sep 19, 2023	Anomaly DetectionAutonomous Driving	CodeCode Available	1
kTrans: Knowledge-Aware Transformer for Binary Code Embedding	Aug 24, 2023	Outlier Detection	CodeCode Available	1
Learning on Graphs with Out-of-Distribution Nodes	Aug 13, 2023	Graph AttentionGraph Learning	CodeCode Available	1
Uncertainty Quantification for Image-based Traffic Prediction across Cities	Aug 11, 2023	Decision MakingDecision Making Under Uncertainty	CodeCode Available	1
Computationally Assisted Quality Control for Public Health Data Streams	Jun 29, 2023	Decision MakingOutlier Detection	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