SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 326–350 of 703 papers

TitleStatusHype
A Review of Change of Variable Formulas for Generative Modeling—0
Cross Domain Image Matching in Presence of Outliers—0
Credit Card Fraud Detection in e-Commerce: An Outlier Detection Approach—0
Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?—0
A Model for Spatial Outlier Detection Based on Weighted Neighborhood Relationship—0
A Deep Learning Anomaly Detection Method in Textual Data—0
Coverage-based Outlier Explanation—0
Are Outlier Detection Methods Resilient to Sampling?—0
Continual Learning with Fully Probabilistic Models—0
Contextual Unsupervised Outlier Detection in Sequences—0
A refined convergence analysis of pDCA_e with applications to simultaneous sparse recovery and outlier detection—0
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model—0
Contextual Outlier Interpretation—0
Defending Object Detectors against Patch Attacks with Out-of-Distribution Smoothing—0
A Rank-Based Similarity Metric for Word Embeddings—0
A Meta-Learning Algorithm for Interrogative Agendas—0
Achieving differential privacy for k-nearest neighbors based outlier detection by data partitioning—0
Integer Programming Relaxations for Integrated Clustering and Outlier Detection—0
Symbiotic Hybrid Neural Network Watchdog For Outlier Detection—0
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach—0
Incremental Outlier Detection Modelling Using Streaming Analytics in Finance & Health Care—0
Improving the Robustness of Federated Learning for Severely Imbalanced Datasets—0
A probabilistic view on Riemannian machine learning models for SPD matrices—0
ALTBI: Constructing Improved Outlier Detection Models via Optimization of Inlier-Memorization Effect—0
Improving Solar Flare Prediction by Time Series Outlier Detection—0
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All datasetsECG5000Balance scale_class 1Breast cancer Wisconsin_class 2Breast cancer Wisconsin_class 4Fashion-MNISTGlass identificationHeart-CHepatitisInternet AdIonosphere_class bSKAB

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VRAE+SVMAccuracy0.98—Unverified
2F-t ALSTM-FCNAccuracy0.95—Unverified
3GENDISAccuracy0.94—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.03—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy37.62—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy65.6—Unverified
#ModelMetricClaimedVerifiedStatus
1PAEAUROC1—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.05—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.93—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy86.33—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMCapsAverage F10.74—Unverified