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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
- 12680
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 0.00013019488
- Overall Rank
- 1,253 | 91.30%
- 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 |
| 4,082 |
Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series |
2023 |
VLDB |
6.4601453e-05 |
| 4,762 |
METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection |
2024 |
VLDB |
5.9338398e-05 |
| 5,785 |
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection |
2024 |
VLDB |
5.3257637e-05 |
| 6,003 |
Time Series Data Mining: A Unifying View |
2023 |
VLDB |
5.2365238e-05 |
| 6,419 |
AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data |
2024 |
VLDB |
5.0621949e-05 |
| 6,435 |
An Experimental Evaluation of Anomaly Detection in Time Series |
2024 |
VLDB |
5.0555305e-05 |
| 7,183 |
TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms |
2022 |
VLDB |
4.8026282e-05 |
| 7,221 |
Akane: Perplexity-Guided Time Series Data Cleaning |
2024 |
SIGMOD |
4.7919849e-05 |
| 7,370 |
Benchmarking the Utility of w-event Differential Privacy Mechanisms - When Baselines Become Mighty Competitors |
2023 |
VLDB |
4.7451678e-05 |
| 8,740 |
A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis |
2024 |
VLDB |
4.4520434e-05 |
| 8,991 |
TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications |
2023 |
VLDB |
4.4113784e-05 |
| 9,558 |
Clean4TSDB: A Data Cleaning Tool for Time Series Databases |
2024 |
VLDB |
4.3212967e-05 |
| 10,061 |
Cleaning Time Series under Seasonal and Trend Constraints |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,451 |
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly Detection |
2025 |
SIGMOD |
4.1905499e-05 |
| 10,578 |
Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains |
2025 |
VLDB |
4.1905499e-05 |
| 10,588 |
Streaming Time Series Subsequence Anomaly Detection: A Glance and Focus Approach |
2025 |
VLDB |
4.1905499e-05 |
| 10,607 |
Time Series Motif Discovery: A Comprehensive Evaluation |
2025 |
VLDB |
4.1905499e-05 |
| 10,645 |
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods |
2025 |
VLDB |
4.1905499e-05 |
| 10,745 |
TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection |
2025 |
VLDB |
4.1905499e-05 |
| 10,834 |
EasyAD: A Demonstration of Automated Solutions for Time-Series Anomaly Detection |
2025 |
VLDB |
4.1905499e-05 |
| 10,880 |
MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection |
2025 |
VLDB |
4.1905499e-05 |
| 11,097 |
Time-Series Anomaly Detection: Overview and New Trends |
2024 |
VLDB |
4.1905499e-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.
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| Overall Rank |
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Year |
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| 10,645 |
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods |
2025 |
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| 2,381 |
TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection |
2022 |
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8.9241557e-05 |
| 8,226 |
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data |
2007 |
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4.5505782e-05 |
| 10,745 |
TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection |
2025 |
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4.1905499e-05 |
| 10,880 |
MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection |
2025 |
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4.1905499e-05 |
| 6,419 |
AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data |
2024 |
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5.0621949e-05 |
| 7,183 |
TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms |
2022 |
VLDB |
4.8026282e-05 |
| 4,082 |
Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series |
2023 |
VLDB |
6.4601453e-05 |
| 11,097 |
Time-Series Anomaly Detection: Overview and New Trends |
2024 |
VLDB |
4.1905499e-05 |
| 6,435 |
An Experimental Evaluation of Anomaly Detection in Time Series |
2024 |
VLDB |
5.0555305e-05 |