SOTAVerified

Time Series Anomaly Detection

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 264 papers

TitleStatusHype
MOSPAT: AutoML based Model Selection and Parameter Tuning for Time Series Anomaly DetectionCode5
The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection BenchmarkCode3
AER: Auto-Encoder with Regression for Time Series Anomaly DetectionCode3
TAB: Unified Benchmarking of Time Series Anomaly Detection MethodsCode2
dtaianomaly: A Python library for time series anomaly detectionCode2
VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly DetectionCode2
CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency PatchingCode2
European Space Agency Benchmark for Anomaly Detection in Satellite TelemetryCode2
Large language models can be zero-shot anomaly detectors for time series?Code2
TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection ModelsCode2
Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency PerspectiveCode2
MTAD: Tools and Benchmarks for Multivariate Time Series Anomaly DetectionCode2
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly DetectionCode2
PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time SeriesCode2
Anomaly Transformer: Time Series Anomaly Detection with Association DiscrepancyCode2
TadGAN: Time Series Anomaly Detection Using Generative Adversarial NetworksCode2
LSTM-based Encoder-Decoder for Multi-sensor Anomaly DetectionCode2
Can Multimodal LLMs Perform Time Series Anomaly Detection?Code1
MAAT: Mamba Adaptive Anomaly Transformer with association discrepancy for time seriesCode1
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment LabelsCode1
F-SE-LSTM: A Time Series Anomaly Detection Method with Frequency Domain InformationCode1
TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly DetectionCode1
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold NetworksCode1
Can LLMs Understand Time Series Anomalies?Code1
Show:102550
← PrevPage 1 of 11Next →
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