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Time Series Anomaly Detection

Papers

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Showing 151–175 of 264 papers

TitleStatusHype
Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection—0
Edge Conditional Node Update Graph Neural Network for Multi-variate Time Series Anomaly Detection—0
DACR: Distribution-Augmented Contrastive Reconstruction for Time-Series Anomaly Detection—0
PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies—0
Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing ValuesCode0
Weakly Augmented Variational Autoencoder in Time Series Anomaly Detection—0
Attention and Autoencoder Hybrid Model for Unsupervised Online Anomaly Detection—0
TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly DetectionCode0
Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection—0
k-Parameter Approach for False In-Season Anomaly Suppression in Daily Time Series Anomaly Detection—0
Sketching Multidimensional Time Series for Fast Discord Mining—0
Few-shot time-series anomaly detection with unsupervised domain adaptation—0
MIM-GAN-based Anomaly Detection for Multivariate Time Series DataCode0
OrionBench: Benchmarking Time Series Generative Models in the Service of the End-UserCode0
Open-Set Multivariate Time-Series Anomaly Detection—0
MST-GAT: A Multimodal Spatial-Temporal Graph Attention Network for Time Series Anomaly Detection—0
DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection—0
LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection—0
Successive Data Injection in Conditional Quantum GAN Applied to Time Series Anomaly Detection—0
Algorithmic Recourse for Anomaly Detection in Multivariate Time Series—0
Generative Pre-Training of Time-Series Data for Unsupervised Fault Detection in Semiconductor Manufacturing—0
MadSGM: Multivariate Anomaly Detection with Score-based Generative Models—0
Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models—0
Low-count Time Series Anomaly Detection—0
Multivariate Time Series Anomaly Detection: Fancy Algorithms and Flawed Evaluation MethodologyCode0
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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