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 51–100 of 703 papers

TitleStatusHype
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier DetectionCode1
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
AdaLAM: Revisiting Handcrafted Outlier DetectionCode1
Deep Clustering based Fair Outlier DetectionCode1
FOUND: Foot Optimization with Uncertain Normals for Surface Deformation Using Synthetic DataCode1
Explainable Deep One-Class ClassificationCode1
Coniferest: a complete active anomaly detection frameworkCode1
Outlier detection in multivariate functional data through a contaminated mixture modelCode1
Explainable outlier detection through decision tree conditioningCode1
Explaining Anomalies Detected by Autoencoders Using SHAPCode1
Learning Energy-Based Models in High-Dimensional Spaces with Multi-scale Denoising Score MatchingCode1
Computationally Assisted Quality Control for Public Health Data StreamsCode1
Handcrafted Outlier Detection RevisitedCode1
Learning on Graphs with Out-of-Distribution NodesCode1
Autoencoding Under Normalization ConstraintsCode1
Fuzzy Granule Density-Based Outlier Detection with Multi-Scale Granular BallsCode1
Zero-Shot Learning Through Cross-Modal TransferCode1
PNI : Industrial Anomaly Detection using Position and Neighborhood InformationCode1
Automating Outlier Detection via Meta-LearningCode1
OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency RegularizationCode1
Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised LearningCode1
Beyond Outlier Detection: Outlier Interpretation by Attention-Guided Triplet Deviation NetworkCode1
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk ControlCode1
Uncertainty Quantification for Image-based Traffic Prediction across CitiesCode1
FairOD: Fairness-aware Outlier DetectionCode0
Fast Incremental SVDD Learning Algorithm with the Gaussian KernelCode0
Fast Unsupervised Deep Outlier Model Selection with HypernetworksCode0
EntropyStop: Unsupervised Deep Outlier Detection with Loss EntropyCode0
A Framework for Clustering Uncertain DataCode0
Estimating Density Models with Truncation Boundaries using Score MatchingCode0
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKACode0
Enhancing Traffic Flow Prediction using Outlier-Weighted AutoEncoders: Handling Real-Time ChangesCode0
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With SupplementCode0
Efficient variational Bayesian neural network ensembles for outlier detectionCode0
A Fast Greedy Algorithm for Outlier MiningCode0
Elastic Similarity and Distance Measures for Multivariate Time SeriesCode0
Robust outlier detection by de-biasing VAE likelihoodsCode0
Adversarial Subspace Generation for Outlier Detection in High-Dimensional DataCode0
Efficient Subspace Search in Data StreamsCode0
ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg"Code0
Adversarially Learned One-Class Classifier for Novelty DetectionCode0
Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative NetworkCode0
Efficient Curation of Invertebrate Image Datasets Using Feature Embeddings and Automatic Size ComparisonCode0
Do Ensembling and Meta-Learning Improve Outlier Detection in Randomized Controlled Trials?Code0
MaxGap Bandit: Adaptive Algorithms for Approximate RankingCode0
D.MCA: Outlier Detection with Explicit Micro-Cluster AssignmentsCode0
Edgewise outliers of network indexed signalsCode0
Efficient Generation of Hidden Outliers for Improved Outlier DetectionCode0
G-PECNet: Towards a Generalizable Pedestrian Trajectory Prediction SystemCode0
Embedding-Based Complex Feature Value Coupling Learning for Detecting Outliers in Non-IID Categorical DataCode0
Show:102550
← PrevPage 2 of 15Next →
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