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Time Series Anomaly Detection

Papers

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Showing 176–200 of 264 papers

TitleStatusHype
DAE : Discriminatory Auto-Encoder for multivariate time-series anomaly detection in air transportation—0
PatchTrAD: A Patch-Based Transformer focusing on Patch-Wise Reconstruction Error for Time Series Anomaly Detection—0
DACR: Distribution-Augmented Contrastive Reconstruction for Time-Series Anomaly Detection—0
Coupled Attention Networks for Multivariate Time Series Anomaly Detection—0
Prototypes as Explanation for Time Series Anomaly Detection—0
PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies—0
Counterfactual Explanation for Auto-Encoder Based Time-Series Anomaly Detection—0
Quantum Autoencoder for Multivariate Time Series Anomaly Detection—0
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection—0
Reconstruct Anomaly to Normal: Adversarial Learned and Latent Vector-constrained Autoencoder for Time-series Anomaly Detection—0
Recurrent Auto-Encoder With Multi-Resolution Ensemble and Predictive Coding for Multivariate Time-Series Anomaly Detection—0
Refining the Optimization Target for Automatic Univariate Time Series Anomaly Detection in Monitoring Services—0
Refining Time Series Anomaly Detectors using Large Language Models—0
RePAD2: Real-Time, Lightweight, and Adaptive Anomaly Detection for Open-Ended Time Series—0
ReRe: A Lightweight Real-time Ready-to-Go Anomaly Detection Approach for Time Series—0
AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection—0
Context-aware Domain Adaptation for Time Series Anomaly Detection—0
RLAD: Time Series Anomaly Detection through Reinforcement Learning and Active Learning—0
Unsupervised Anomaly Detection in Time-series: An Extensive Evaluation and Analysis of State-of-the-art Methods—0
Robust Anomaly Detection for Time-series Data—0
Robust Learning of Deep Time Series Anomaly Detection Models with Contaminated Training Data—0
Unsupervised Distance Metric Learning for Anomaly Detection Over Multivariate Time Series—0
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks—0
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directions—0
RoLA: A Real-Time Online Lightweight Anomaly Detection System for Multivariate Time Series—0
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All datasetsUCR Anomaly ArchiveKPIMSLSMAPSMDSWaTWADIYahoo A1

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TimeVQVAE-ADaccuracy0.71—Unverified
2Matrix Profile STUMPYaccuracy0.51—Unverified
3MDIaccuracy0.47—Unverified
4Matrix Profile SCRIMPaccuracy0.42—Unverified
5RCFaccuracy0.39—Unverified
6IFaccuracy0.38—Unverified
7Convolutional AEaccuracy0.35—Unverified
8SR-CNNaccuracy0.3—Unverified
9USADaccuracy0.28—Unverified
10AEaccuracy0.24—Unverified
#ModelMetricClaimedVerifiedStatus
1CARLAAUPR0.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CARLAAUPR0.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CARLAAUPR0.45—Unverified
#ModelMetricClaimedVerifiedStatus
1CARLAAUPR0.51—Unverified
#ModelMetricClaimedVerifiedStatus
1CARLAAUPR0.68—Unverified
#ModelMetricClaimedVerifiedStatus
1CARLAAUPR0.13—Unverified
#ModelMetricClaimedVerifiedStatus
1CARLAAUPR0.65—Unverified