Time Series Anomaly Detection

Benchmarks archive 2025-07-28

8 leaderboard tables shown for this task, 8 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

10 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 127 papers with code (264 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• AA-Forecast: Anomaly-Aware Forecast for Extreme Events
  21 Aug 2022 9 repositories listed
  Moreover, the framework employs a dynamic uncertainty optimization algorithm that reduces the uncertainty of forecasts in an online manner.
• LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection
  1 Jul 2016 8 repositories listed Syntology ran 1 of 9 samples · 8 unverified
  Mechanical devices such as engines, vehicles, aircrafts, etc., are typically instrumented with numerous sensors to capture the behavior and health of the machine.
• Deep and Confident Prediction for Time Series at Uber
  6 Sep 2017 6 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Reliable uncertainty estimation for time series prediction is critical in many fields, including physics, biology, and manufacturing.
• PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series
  30 May 2023 5 repositories listed Syntology ran 0 of 21 samples · 21 unverified
  PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series, i.
• TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
  16 Sep 2020 5 repositories listed
  However, detecting anomalies in time series data is particularly challenging due to the vague definition of anomalies and said data's frequent lack of labels and highly complex temporal correlations.
• A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data
  20 Nov 2018 5 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Subsequently, given the signature matrices, a convolutional encoder is employed to encode the inter-sensor (time series) correlations and an attention based Convolutional Long-Short Term Memory (ConvLSTM) network is…
• TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly Detection
  3 Apr 2024 4 repositories listed
  A two-fold challenge for TSAD is a versatile and unsupervised model that can detect various different types of time series anomalies (spikes, discontinuities, trend shifts, etc.)
• DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series
  19 Dec 2018 4 repositories listed
  In contrast to the anomaly detection methods where anomalies are learned, DeepAnT uses unlabeled data to capture and learn the data distribution that is used to forecast the normal behavior of a time series.
• AER: Auto-Encoder with Regression for Time Series Anomaly Detection
  27 Dec 2022 3 repositories listed
  We then propose AER (Auto-encoder with Regression), a joint model that combines a vanilla auto-encoder and an LSTM regressor to incorporate the successes and address the limitations of each method.
• Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
  6 Oct 2021 3 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  Unsupervised detection of anomaly points in time series is a challenging problem, which requires the model to derive a distinguishable criterion.
• Time-Series Anomaly Detection Service at Microsoft
  10 Jun 2019 3 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  At Microsoft, we develop a time-series anomaly detection service which helps customers to monitor the time-series continuously and alert for potential incidents on time.
• TAB: Unified Benchmarking of Time Series Anomaly Detection Methods
  22 Jun 2025 2 repositories listed Syntology ran 4 of 6 samples · 2 unverified · 6 pointer-only (licence)
  Time series anomaly detection (TSAD) plays an important role in many domains such as finance, transportation, and healthcare.
• TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Models
  16 Feb 2024 2 repositories listed Syntology ran 2 of 6 samples · 4 unverified · 6 pointer-only (licence)
  The performance of testing newly incoming unseen time series on current TSAD algorithms remains unknown.
• DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection
  17 Jun 2023 2 repositories listed
  On the other hand, contrastive learning aims to find a representation that can clearly distinguish any instance from the others, which can bring a more natural and promising representation for time series anomaly…
• Window Size Selection in Unsupervised Time Series Analytics: A Review and Benchmark
  4 Feb 2023 2 repositories listed
  We provide, for the first time, a systematic survey and experimental study of 6 TS window size selection (WSS) algorithms on three diverse TSDM tasks, namely anomaly detection, segmentation and motif discovery, using…
• Deep Learning for Time Series Anomaly Detection: A Survey
  9 Nov 2022 2 repositories listed Syntology ran 0 of 15 samples · 15 unverified
  Time series anomaly detection has applications in a wide range of research fields and applications, including manufacturing and healthcare.
• Detecting Multivariate Time Series Anomalies with Zero Known Label
  3 Aug 2022 2 repositories listed
  Multivariate time series anomaly detection has been extensively studied under the semi-supervised setting, where a training dataset with all normal instances is required.
• Multivariate Time-series Anomaly Detection via Graph Attention Network
  4 Sep 2020 2 repositories listed Syntology ran 3 of 8 samples · 5 unverified
  Anomaly detection on multivariate time-series is of great importance in both data mining research and industrial applications.
• Anomaly Detection for Time Series Using VAE-LSTM Hybrid Model
  9 Apr 2020 2 repositories listed
  In this work, we propose a VAE-LSTM hybrid model as an unsupervised approach for anomaly detection in time series.
• mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
  26 Jun 2025 1 repository listed
  Multivariate time series anomaly detection (MTS-AD) is critical in domains like healthcare, cybersecurity, and industrial monitoring, yet remains challenging due to complex inter-variable dependencies, temporal…
• Benchmarking Unsupervised Strategies for Anomaly Detection in Multivariate Time Series
  25 Jun 2025 1 repository listed
  Anomaly detection in multivariate time series is an important problem across various fields such as healthcare, financial services, manufacturing or physics detector monitoring.
• RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated Data
  24 Mar 2025 1 repository listed
  It fuses the separated assumptions of one-class classification and contrastive learning in a single training process to characterize a more complete so-called normality.
• KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly Detection
  16 Mar 2025 1 repository listed
  Model selection has been raised as an essential problem in the area of time series anomaly detection (TSAD), because there is no single best TSAD model for the highly heterogeneous time series in real-world applications.
• OIPR: Evaluation for Time-series Anomaly Detection Inspired by Operator Interest
  3 Mar 2025 1 repository listed
  Furthermore, we build a special scenario dataset to compare the characteristics of different evaluation methods.
• Can Multimodal LLMs Perform Time Series Anomaly Detection?
  25 Feb 2025 1 repository listed
  Starting with the univariate case (point- and range-wise anomalies), we extend our evaluation to more practical scenarios, including multivariate and irregular time series scenarios, and variate-wise anomalies.
• dtaianomaly: A Python library for time series anomaly detection
  20 Feb 2025 1 repository listed
  dtaianomaly is an open-source Python library for time series anomaly detection, designed to bridge the gap between academic research and real-world applications.
• VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly Detection
  18 Feb 2025 1 repository listed
  Anomaly detection (AD) is a fundamental task for time-series analytics with important implications for the downstream performance of many applications.
• MAAT: Mamba Adaptive Anomaly Transformer with association discrepancy for time series
  11 Feb 2025 1 repository listed
  Anomaly detection in time series is essential for industrial monitoring and environmental sensing, yet distinguishing anomalies from complex patterns remains challenging.
• Federated Learning with Reservoir State Analysis for Time Series Anomaly Detection
  8 Feb 2025 1 repository listed
  The results show that IncFed MD-RS outperforms other federated learning methods with deep learning and reservoir computing models particularly when clients' data are relatively short and heterogeneous.
• GDformer: Going Beyond Subsequence Isolation for Multivariate Time Series Anomaly Detection
  30 Jan 2025 1 repository listed
  Unsupervised anomaly detection of multivariate time series is a challenging task, given the requirements of deriving a compact detection criterion without accessing the anomaly points.

Syntology lines on 10 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.