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Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection
Summary: TSB-UAD benchmark for univariate time-series anomaly detection; 12 methods, 1980 series, 13 accuracy measures. Theseus: modular web app to navigate benchmark, compare methods and metrics across conditions, aiding method selection.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12867
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 4.3608061e-05
- Overall Rank
- 9,294 | 35.35%
- DOI
-
10.14778/3554821.3554879
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 11 of 11 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 |
| 5,777 |
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection |
2024 |
VLDB |
5.3308813e-05 |
| 9,329 |
Odyssey: An Engine Enabling The Time-Series Clustering Journey |
2023 |
VLDB |
4.3556432e-05 |
| 9,599 |
SPARTAN: Data-Adaptive Symbolic Time-Series Approximation |
2025 |
SIGMOD |
4.3177432e-05 |
| 10,466 |
A Structured Study of Multivariate Time-Series Distance Measures |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,524 |
Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Tabular Data |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,738 |
TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection |
2025 |
VLDB |
4.1945683e-05 |
| 10,739 |
Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods |
2025 |
VLDB |
4.1945683e-05 |
| 10,741 |
Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression |
2025 |
VLDB |
4.1945683e-05 |
| 11,094 |
Time-Series Anomaly Detection: Overview and New Trends |
2024 |
VLDB |
4.1945683e-05 |
| 11,235 |
Accelerating Similarity Search for Elastic Measures: A Study and New Generalization of Lower Bounding Distances |
2023 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 1,516 |
k-Shape: Efficient and Accurate Clustering of Time Series |
2015 |
SIGMOD |
0.00011586255 |
| 2,029 |
SAND: Streaming Subsequence Anomaly Detection |
2021 |
VLDB |
9.740868e-05 |
| 2,381 |
TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection |
2022 |
VLDB |
8.9327638e-05 |
| 2,613 |
Decomposed Bounded Floats for Fast Compression and Queries |
2021 |
VLDB |
8.4503824e-05 |
| 2,644 |
Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series |
2020 |
VLDB |
8.3832357e-05 |
| 3,943 |
Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection |
2022 |
VLDB |
6.6099833e-05 |
| 4,059 |
GRAIL: Efficient Time-Series Representation Learning |
2019 |
VLDB |
6.4854417e-05 |
| 4,853 |
Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures |
2020 |
SIGMOD |
5.8760276e-05 |
| 6,311 |
VergeDB: A Database for IoT Analytics on Edge Devices |
2021 |
CIDR |
5.1161316e-05 |
| 6,367 |
Good to the Last Bit: Data-Driven Encoding with CodecDB |
2021 |
SIGMOD |
5.0941072e-05 |
| 8,088 |
PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage |
2020 |
VLDB |
4.5897316e-05 |
| 13,261 |
SAND in Action: Subsequence Anomaly Detection for Streams |
2021 |
VLDB |
- |
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Paper |
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Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series |
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0.00011058945 |
| 6,423 |
AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data |
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Anomaly Detection in Time Series: A Comprehensive Evaluation |
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| 11,094 |
Time-Series Anomaly Detection: Overview and New Trends |
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TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection |
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| 2,381 |
TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection |
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VLDB |
8.9327638e-05 |