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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1501–1510 of 4856 papers

Title	Date	Tasks	Status	Score
Federated Learning with Reservoir State Analysis for Time Series Anomaly Detection	Feb 8, 2025	Anomaly DetectionComputational Efficiency	CodeCode Available	5
Hyperedge Anomaly Detection with Hypergraph Neural Network	Dec 7, 2024	Anomaly DetectionLink Prediction	CodeCode Available	5
Explainable Debugger for Black-box Machine Learning Models	Jul 18, 2021	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	5
ALFA: A Dataset for UAV Fault and Anomaly Detection	Jul 14, 2019	Anomaly DetectionFault Detection	CodeCode Available	5
Explainable Differential Privacy-Hyperdimensional Computing for Balancing Privacy and Transparency in Additive Manufacturing Monitoring	Jul 9, 2024	Anomaly DetectionDefect Detection	CodeCode Available	5
Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly Detection	Jan 25, 2016	Anomaly DetectionIncremental Learning	CodeCode Available	5
Experiment-based detection of service disruption attacks in optical networks using data analytics and unsupervised learning	Feb 1, 2019	Anomaly DetectionClustering	CodeCode Available	5
Explainable Anomaly Detection for Industrial Control System Cybersecurity	May 4, 2022	Anomaly DetectionExplainable artificial intelligence	CodeCode Available	5
Explainable Machine Learning for Cyberattack Identification from Traffic Flows	May 2, 2025	Anomaly DetectionManagement	CodeCode Available	5
Exact Optimization of Conformal Predictors via Incremental and Decremental Learning	Feb 5, 2021	Anomaly Detectionregression	CodeCode Available	5

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All datasets MVTec AD VisA MVTec LOCO AD One-class CIFAR-10 CUHK Avenue ShanghaiTech Fishyscapes L&F UCR Anomaly Archive MPDD BTAD One-class CIFAR-100 UBnormal

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	CPR-faster(TensorRT)	FPS	1,016	—	Unverified
2	CPR-fast(TensorRT)	FPS	362	—	Unverified
3	CPR(TensorRT)	FPS	130	—	Unverified
4	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	Detection AUROC	99.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UniNet	Detection AUROC	99.8	—	Unverified
2	GLAD	Detection AUROC	99.5	—	Unverified
3	UniNet(model-unified multi-class)	Detection AUROC	99.15	—	Unverified
4	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
7	DiffusionAD	Detection AUROC	98.8	—	Unverified
8	GLASS	Detection AUROC	98.8	—	Unverified
9	TransFusion	Detection AUROC	98.7	—	Unverified
10	HETMM	Detection AUROC	98.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CSAD	Avg. Detection AUROC	95.3	—	Unverified
2	PSAD	Avg. Detection AUROC	94.9	—	Unverified