SOTAVerified

Anomaly Detection

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

Papers

Showing 16261650 of 4856 papers

TitleStatusHype
Effective and Efficient Representation Learning for Flight TrajectoriesCode0
Early-Stage Anomaly Detection: A Study of Model Performance on Complete vs. Partial FlowsCode0
Bridging 3D Anomaly Localization and Repair via High-Quality Continuous Geometric RepresentationCode0
Are you sure it’s an artifact? Artifact detection and uncertainty quantification in histological imagesCode0
robROSE: A robust approach for dealing with imbalanced data in fraud detectionCode0
Polynomial Selection in Spectral Graph Neural Networks: An Error-Sum of Function Slices ApproachCode0
Breast Cancer Detection Using Convolutional Neural NetworksCode0
E-ABIN: an Explainable module for Anomaly detection in BIological NetworksCode0
Robust Subspace Recovery Layer for Unsupervised Anomaly DetectionCode0
Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep UnrollingCode0
Adaptive NAD: Online and Self-adaptive Unsupervised Network Anomaly DetectorCode0
Detector monitoring with artificial neural networks at the CMS experiment at the CERN Large Hadron ColliderCode0
Rule-Based Error Detection and Correction to Operationalize Movement Trajectory ClassificationCode0
Action Sequence Augmentation for Early Graph-based Anomaly DetectionCode0
Anomaly detection in dynamic networksCode0
SAM-kNN Regressor for Online Learning in Water Distribution NetworksCode0
Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier featuresCode0
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health EpisodesCode0
Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory TracingCode0
Coupled-Space Attacks against Random-Walk-based Anomaly DetectionCode0
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal PropertiesCode0
Braced Fourier Continuation and Regression for Anomaly DetectionCode0
Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection SimplifiedCode0
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated LearningCode0
Adaptive Anomaly Detection in Chaotic Time Series with a Spatially Aware Echo State NetworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified