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 241–250 of 703 papers

Title	Date	Tasks	Status
Annealed Denoising score matching: learning Energy based model in high-dimensional spaces	Sep 25, 2019	DenoisingImage Inpainting	—Unverified
ECO-AMLP: A Decision Support System using an Enhanced Class Outlier with Automatic Multilayer Perceptron for Diabetes Prediction	Jun 23, 2017	Diabetes PredictionDisease Prediction	—Unverified
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning	Jun 19, 2020	Fraud Detectionimage-classification	—Unverified
DRGRADUATE: uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images	Oct 25, 2019	Diabetic Retinopathy GradingMultiple Instance Learning	—Unverified
Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?	May 19, 2021	Outlier DetectionRepresentation Learning	—Unverified
EDoG: Adversarial Edge Detection For Graph Neural Networks	Dec 27, 2022	Drug DesignEdge Detection	—Unverified
An Isolation Forest Learning Based Outlier Detection Approach for Effectively Classifying Cyber Anomalies	Dec 9, 2020	Intrusion DetectionOutlier Detection	—Unverified
A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity	Jul 1, 2018	Named Entity Recognition (NER)Outlier Detection	—Unverified
Active Relation Discovery: Towards General and Label-aware Open Relation Extraction	Nov 8, 2022	Active LearningOutlier Detection	—Unverified
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions	Apr 8, 2021	Outlier DetectionOut of Distribution (OOD) 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