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Time Series Anomaly Detection

Papers

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Showing 151–200 of 264 papers

TitleStatusHype
Enhancing Network Anomaly Detection with Quantum GANs and Successive Data Injection for Multivariate Time Series—0
MST-GAT: A Multimodal Spatial-Temporal Graph Attention Network for Time Series Anomaly Detection—0
Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis—0
Edge Conditional Node Update Graph Neural Network for Multi-variate Time Series Anomaly Detection—0
Weakly Augmented Variational Autoencoder in Time Series Anomaly Detection—0
MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast—0
Do Deep Neural Networks Contribute to Multivariate Time Series Anomaly Detection?—0
Diverse Counterfactual Explanations for Anomaly Detection in Time Series—0
Multivariate Time Series Anomaly Detection via Dynamic Graph Forecasting—0
Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models—0
AMAD: AutoMasked Attention for Unsupervised Multivariate Time Series Anomaly Detection—0
Devil in the Detail: Attack Scenarios in Industrial Applications—0
Algorithmic Recourse for Anomaly Detection in Multivariate Time Series—0
Multivariate Time Series Anomaly Detection in Industry 5.0—0
ALGAN: Time Series Anomaly Detection with Adjusted-LSTM GAN—0
DeepFIB: Self-Imputation for Time Series Anomaly Detection—0
Deep Baseline Network for Time Series Modeling and Anomaly Detection—0
NVAE-GAN Based Approach for Unsupervised Time Series Anomaly Detection—0
Understanding Time Series Anomaly State Detection through One-Class Classification—0
DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection—0
Online Model-based Anomaly Detection in Multivariate Time Series: Taxonomy, Survey, Research Challenges and Future Directions—0
OnlineSTL: Scaling Time Series Decomposition by 100x—0
Online Time Series Anomaly Detection with State Space Gaussian Processes—0
Open-Set Multivariate Time-Series Anomaly Detection—0
Advancing Cyber-Attack Detection in Power Systems: A Comparative Study of Machine Learning and Graph Neural Network Approaches—0
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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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