Back to papers
Anomaly Detection in Time Series: A Comprehensive Evaluation
Summary: Comprehensive, large-scale empirical study re-implements 71 anomaly detectors for time series. Evaluated on 976 datasets, analyzes effectiveness, efficiency, and robustness across families; provides guidance for detector selection and suggests future research directions.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12679
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 0.00013032074
- Overall Rank
- 1,253 | 91.29%
- DOI
-
10.14778/3538598.3538602
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 22 of 22 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 4,079 |
Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series |
2023 |
VLDB |
6.4663636e-05 |
| 4,762 |
METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection |
2024 |
VLDB |
5.9395463e-05 |
| 5,777 |
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection |
2024 |
VLDB |
5.3308813e-05 |
| 5,999 |
Time Series Data Mining: A Unifying View |
2023 |
VLDB |
5.2415551e-05 |
| 6,423 |
AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data |
2024 |
VLDB |
5.0670573e-05 |
| 6,440 |
An Experimental Evaluation of Anomaly Detection in Time Series |
2024 |
VLDB |
5.0603878e-05 |
| 7,182 |
TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms |
2022 |
VLDB |
4.8072409e-05 |
| 7,223 |
Akane: Perplexity-Guided Time Series Data Cleaning |
2024 |
SIGMOD |
4.7965857e-05 |
| 7,371 |
Benchmarking the Utility of w-event Differential Privacy Mechanisms - When Baselines Become Mighty Competitors |
2023 |
VLDB |
4.7497236e-05 |
| 8,744 |
A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis |
2024 |
VLDB |
4.456315e-05 |
| 8,985 |
TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications |
2023 |
VLDB |
4.4156106e-05 |
| 9,558 |
Clean4TSDB: A Data Cleaning Tool for Time Series Databases |
2024 |
VLDB |
4.3254416e-05 |
| 10,061 |
Cleaning Time Series under Seasonal and Trend Constraints |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,441 |
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly Detection |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,569 |
Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains |
2025 |
VLDB |
4.1945683e-05 |
| 10,579 |
Streaming Time Series Subsequence Anomaly Detection: A Glance and Focus Approach |
2025 |
VLDB |
4.1945683e-05 |
| 10,599 |
Time Series Motif Discovery: A Comprehensive Evaluation |
2025 |
VLDB |
4.1945683e-05 |
| 10,637 |
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods |
2025 |
VLDB |
4.1945683e-05 |
| 10,738 |
TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection |
2025 |
VLDB |
4.1945683e-05 |
| 10,830 |
EasyAD: A Demonstration of Automated Solutions for Time-Series Anomaly Detection |
2025 |
VLDB |
4.1945683e-05 |
| 10,876 |
MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection |
2025 |
VLDB |
4.1945683e-05 |
| 11,094 |
Time-Series Anomaly Detection: Overview and New Trends |
2024 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 10,637 |
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods |
2025 |
VLDB |
4.1945683e-05 |
| 2,381 |
TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection |
2022 |
VLDB |
8.9327638e-05 |
| 8,228 |
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data |
2007 |
VLDB |
4.5549459e-05 |
| 10,738 |
TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection |
2025 |
VLDB |
4.1945683e-05 |
| 10,876 |
MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection |
2025 |
VLDB |
4.1945683e-05 |
| 6,423 |
AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data |
2024 |
VLDB |
5.0670573e-05 |
| 7,182 |
TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms |
2022 |
VLDB |
4.8072409e-05 |
| 4,079 |
Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series |
2023 |
VLDB |
6.4663636e-05 |
| 11,094 |
Time-Series Anomaly Detection: Overview and New Trends |
2024 |
VLDB |
4.1945683e-05 |
| 6,440 |
An Experimental Evaluation of Anomaly Detection in Time Series |
2024 |
VLDB |
5.0603878e-05 |