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 42014225 of 4856 papers

TitleStatusHype
Approaches Toward Physical and General Video Anomaly DetectionCode0
Introduction to Rare-Event Predictive Modeling for Inferential Statisticians -- A Hands-On Application in the Prediction of Breakthrough PatentsCode0
Interruptions detection in video conferencesCode0
A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum ProcessorCode0
Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory ModelsCode0
Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking StudyCode0
TRANSIT your events into a new mass: Fast background interpolation for weakly-supervised anomaly searchesCode0
Digital Twin-Based Multiple Access Optimization and Monitoring via Model-Driven Bayesian LearningCode0
Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical SystemsCode0
Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networksCode0
Can I trust my anomaly detection system? A case study based on explainable AICode0
Interdependency Matters: Graph Alignment for Multivariate Time Series Anomaly DetectionCode0
Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature PerturbationCode0
Maximum Entropy Generators for Energy-Based ModelsCode0
Integrating Quantum-Classical Attention in Patch Transformers for Enhanced Time Series ForecastingCode0
TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly DetectionCode0
InQMAD: Incremental Quantum Measurement Anomaly DetectionCode0
A One-Class Classification method based on Expanded Non-Convex HullsCode0
Input complexity and out-of-distribution detection with likelihood-based generative modelsCode0
Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly DetectionCode0
InForecaster: Forecasting Influenza Hemagglutinin Mutations Through the Lens of Anomaly DetectionCode0
Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor WatermarkingCode0
Value Gradient Sampler: Sampling as Sequential Decision MakingCode0
Representation Learning for Time-Domain High-Energy Astrophysics: Discovery of Extragalactic Fast X-ray Transient XRT 200515Code0
Surface Defect Saliency of Magnetic TileCode0
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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