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

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Showing 401–450 of 4856 papers

TitleStatusHype
Value Gradient Sampler: Sampling as Sequential Decision MakingCode0
VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly DetectionCode2
A Survey of Anomaly Detection in Cyber-Physical Systems—0
Positional Encoding in Transformer-Based Time Series Models: A SurveyCode1
Towards a Trustworthy Anomaly Detection for Critical Applications through Approximated Partial AUC LossCode0
Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection—0
WRT-SAM: Foundation Model-Driven Segmentation for Generalized Weld Radiographic Testing—0
DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly DetectionCode0
Unifying Explainable Anomaly Detection and Root Cause Analysis in Dynamical Systems—0
Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset—0
Exploiting Point-Language Models with Dual-Prompts for 3D Anomaly Detection—0
Federated Learning-Driven Cybersecurity Framework for IoT Networks with Privacy-Preserving and Real-Time Threat Detection Capabilities—0
Enhancing anomaly detection with topology-aware autoencoders—0
Privacy-Preserving Hybrid Ensemble Model for Network Anomaly Detection: Balancing Security and Data Protection—0
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly DetectionCode1
Unsupervised Anomaly Detection on Implicit Shape representations for Sarcopenia Detection—0
GenIAS: Generator for Instantiating Anomalies in time Series—0
CurvGAD: Leveraging Curvature for Enhanced Graph Anomaly Detection—0
Out-of-Distribution Detection on Graphs: A SurveyCode1
MAAT: Mamba Adaptive Anomaly Transformer with association discrepancy for time seriesCode1
Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Data—0
Advancing climate model interpretability: Feature attribution for Arctic melt anomalies—0
FADE: Forecasting for Anomaly Detection on ECGCode0
Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models—0
Towards Copyright Protection for Knowledge Bases of Retrieval-augmented Language Models via Reasoning—0
Multimodal Task Representation Memory Bank vs. Catastrophic Forgetting in Anomaly Detection—0
Foundation Models for Anomaly Detection: Vision and Challenges—0
SAFE: Self-Supervised Anomaly Detection Framework for Intrusion Detection—0
Leveraging GPT-4o Efficiency for Detecting Rework Anomaly in Business Processes—0
3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised AnomalyCode2
Federated Learning with Reservoir State Analysis for Time Series Anomaly DetectionCode0
Aero-engines Anomaly Detection using an Unsupervised Fisher Autoencoder—0
Multi-scale Masked Autoencoder for Electrocardiogram Anomaly Detection—0
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated LearningCode0
DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions—0
Federated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks—0
Position: Untrained Machine Learning for Anomaly Detection—0
Finding Pegasus: Enhancing Unsupervised Anomaly Detection in High-Dimensional Data using a Manifold-Based Approach—0
From Bedside to Desktop: A Data Protocol for Normative Intracranial EEG and Abnormality Mapping—0
NLP-Based .NET CLR Event Logs AnalyzerCode0
SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited LabelsCode1
General Time-series Model for Universal Knowledge Representation of Multivariate Time-Series data—0
Aero-LLM: A Distributed Framework for Secure UAV Communication and Intelligent Decision-Making—0
TopoCL: Topological Contrastive Learning for Time Series—0
Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning—0
Complying with the EU AI Act: Innovations in Explainable and User-Centric Hand Gesture Recognition—0
Anomaly Detection via Autoencoder Composite Features and NCE—0
LAST SToP For Modeling Asynchronous Time Series—0
A Poisson Process AutoDecoder for X-ray Sources—0
ConditionNET: Learning Preconditions and Effects for Execution Monitoring—0
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All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
7DDADDetection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9PBASDetection AUROC99.8—Unverified
10HETMMDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4DDADDetection AUROC98.9—Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
6INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified