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 48264850 of 4856 papers

TitleStatusHype
Spatio-temporal Multivariate Cluster Evolution Analysis for Detecting and Tracking Climate ImpactsCode0
AD-DMKDE: Anomaly Detection through Density Matrices and Fourier FeaturesCode0
Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked AutoencoderCode0
Anomaly Detection for Hybrid Butterfly Subspecies via Probability FilteringCode0
Assessing the Impact of a Supervised Classification Filter on Flow-based Hybrid Network Anomaly DetectionCode0
SpectNet : End-to-End Audio Signal Classification Using Learnable SpectrogramsCode0
Quantum-probabilistic Hamiltonian learning for generative modelling & anomaly detectionCode0
A Showcase of the Use of Autoencoders in Feature Learning ApplicationsCode0
QBSD: Quartile-Based Seasonality Decomposition for Cost-Effective RAN KPI ForecastingCode0
Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph LaplacianCode0
Towards Unbiased Evaluation of Time-series Anomaly DetectorCode0
Action Sequence Augmentation for Early Graph-based Anomaly DetectionCode0
Composite Convolution: a Flexible Operator for Deep Learning on 3D Point CloudsCode0
Quorum: Zero-Training Unsupervised Anomaly Detection using Quantum AutoencodersCode0
E-ABIN: an Explainable module for Anomaly detection in BIological NetworksCode0
R2-AD2: Detecting Anomalies by Analysing the Raw GradientCode0
Adaptive NAD: Online and Self-adaptive Unsupervised Network Anomaly DetectorCode0
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal PropertiesCode0
Dynamic Erasing Network Based on Multi-Scale Temporal Features for Weakly Supervised Video Anomaly DetectionCode0
Coupled-Space Attacks against Random-Walk-based Anomaly DetectionCode0
Vision Transformers for Small Histological Datasets Learned through Knowledge DistillationCode0
A Computational Theory and Semi-Supervised Algorithm for ClusteringCode0
Comparison of Anomaly Detectors: Context MattersCode0
SplatPose+: Real-time Image-Based Pose-Agnostic 3D Anomaly DetectionCode0
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time SeriesCode0
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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