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

Showing 501525 of 703 papers

TitleStatusHype
GENDIS: GENetic DIscovery of ShapeletsCode0
A Study of Deep Learning for Network Traffic Data Forecasting0
Outlier Detection in High Dimensional Data0
Cross Domain Image Matching in Presence of Outliers0
A Robust Regression Approach for Robot Model Learning0
What goes around comes around: Cycle-Consistency-based Short-Term Motion Prediction for Anomaly Detection using Generative Adversarial Networks0
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain ShiftCode0
Are Outlier Detection Methods Resilient to Sampling?0
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-IIICode0
Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type DataCode0
Embedding-Based Complex Feature Value Coupling Learning for Detecting Outliers in Non-IID Categorical DataCode0
Using Self-Supervised Learning Can Improve Model Robustness and UncertaintyCode0
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier DetectionCode0
AI-enabled Blockchain: An Outlier-aware Consensus Protocol for Blockchain-based IoT Networks0
Anomaly Detection with HMM Gauge Likelihood Analysis0
Radio Galaxy Zoo: Unsupervised Clustering of Convolutionally Auto-encoded Radio-astronomical Images0
Nonconvex Approach for Sparse and Low-Rank Constrained Models with Dual Momentum0
Deep Semi-Supervised Anomaly DetectionCode0
MaxGap Bandit: Adaptive Algorithms for Approximate RankingCode0
Consensus Clustering: An Embedding Perspective, Extension and Beyond0
Robust Variational Autoencoder0
Automated detection of business-relevant outliers in e-commerce conversion rate0
Prediction and outlier detection in classification problems0
Unsupervised routine discovery in egocentric photo-streams0
Outlier Detection from Image Data0
Show:102550
← PrevPage 21 of 29Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VRAE+SVMAccuracy0.98Unverified
2F-t ALSTM-FCNAccuracy0.95Unverified
3GENDISAccuracy0.94Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.03Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy37.62Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy65.6Unverified
#ModelMetricClaimedVerifiedStatus
1PAEAUROC1Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.05Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC0.86Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.85Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.93Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy86.33Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMCapsAverage F10.74Unverified