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Time Series Anomaly Detection

Papers

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Showing 101–150 of 264 papers

TitleStatusHype
GenIAS: Generator for Instantiating Anomalies in time Series—0
Federated Learning with Reservoir State Analysis for Time Series Anomaly DetectionCode0
GDformer: Going Beyond Subsequence Isolation for Multivariate Time Series Anomaly DetectionCode0
Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models—0
GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality—0
Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection—0
Multivariate Time Series Anomaly Detection using DiffGAN ModelCode0
Counterfactual Explanation for Auto-Encoder Based Time-Series Anomaly Detection—0
Dive into Time-Series Anomaly Detection: A Decade ReviewCode0
Graph Mixture of Experts and Memory-augmented Routers for Multivariate Time Series Anomaly Detection—0
PASTA: Neural Architecture Search for Anomaly Detection in Multivariate Time SeriesCode0
A New Perspective on Time Series Anomaly Detection: Faster Patch-based Broad Learning System—0
From CNN to CNN + RNN: Adapting Visualization Techniques 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
See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers—0
Advancing Cyber-Attack Detection in Power Systems: A Comparative Study of Machine Learning and Graph Neural Network Approaches—0
MIXAD: Memory-Induced Explainable Time Series Anomaly DetectionCode0
Hypergraph-based multi-scale spatio-temporal graph convolution network for Time-Series anomaly detection—0
MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast—0
Interdependency Matters: Graph Alignment for Multivariate Time Series Anomaly DetectionCode0
Applying Quantum Autoencoders for Time Series Anomaly Detection—0
Towards Unbiased Evaluation of Time-series Anomaly DetectorCode0
Matrix Profile for Anomaly Detection on Multidimensional Time Series—0
Training-Free Time-Series Anomaly Detection: Leveraging Image Foundation Models—0
Unveiling the Flaws: A Critical Analysis of Initialization Effect on Time Series Anomaly Detection—0
Online Model-based Anomaly Detection in Multivariate Time Series: Taxonomy, Survey, Research Challenges and Future Directions—0
Can LLMs Serve As Time Series Anomaly Detectors?—0
Time Series Anomaly Detection with CNN for Environmental Sensors in Healthcare-IoT—0
Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-time Lightweight Time Series Anomaly Detection—0
Infinite-dimensional Mahalanobis Distance with Applications to Kernelized Novelty DetectionCode0
An Autoencoder Architecture for L-band Passive Microwave Retrieval of Landscape Freeze-Thaw CycleCode0
Self-Supervised Time-Series Anomaly Detection Using Learnable Data Augmentation—0
Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System TelemetryCode0
Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models—0
ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-Variable Context EncodingCode0
Joint Selective State Space Model and Detrending for Robust Time Series Anomaly DetectionCode0
Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders—0
Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection—0
DeepHYDRA: Resource-Efficient Time-Series Anomaly Detection in Dynamically-Configured SystemsCode0
RESTAD: REconstruction and Similarity based Transformer for time series Anomaly DetectionCode0
A Reliable Framework for Human-in-the-Loop Anomaly Detection in Time Series—0
Sub-Adjacent Transformer: Improving Time Series Anomaly Detection with Reconstruction Error from Sub-Adjacent NeighborhoodsCode0
Warped Time Series Anomaly Detection—0
Fault Detection in Mobile Networks Using Diffusion Models—0
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly DetectionCode0
From Chaos to Clarity: Time Series Anomaly Detection in Astronomical ObservationsCode0
Exploring the Influence of Dimensionality Reduction on Anomaly Detection Performance in Multivariate Time SeriesCode0
Unsupervised Distance Metric Learning for Anomaly Detection Over Multivariate Time Series—0
Towards efficient deep autoencoders for multivariate time series anomaly detection—0
Understanding Time Series Anomaly State Detection through One-Class Classification—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