DBScholar

Back to papers

TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

Summary: TranAD applies attention-based Transformer encoders to multivariate time-series anomaly detection and diagnosis, combining focus-score self-conditioning with adversarial training for robust, fast inference. MAML enables data-efficient learning, outperforming baselines by up to 17% F1 while cutting training time 99%. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
hdd8b70aa0dbc59e2
Venue
VLDB
Year
2022
Pagerank
9.7393078e-05
Overall Rank
1,742 | 88.30%
DOI
10.14778/3514061.3514067
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{tuli_vldb22,
        title = {{TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data}},
        author = {Tuli, Shreshth and Casale, Giuliano and Jennings, Nicholas R.},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {6},
        pages = {1201--1214},
        doi = {10.14778/3514061.3514067},
        url = {https://doi.org/10.14778/3514061.3514067},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 20 of 20 citing papers.

Rank Citing Paper Year Venue Pagerank
3,074 BigST: Linear Complexity Spatio-Temporal Graph Neural Network for Traffic Forecasting on Large-Scale Road Networks 2024 VLDB 7.6758241e-05
4,352 Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity 2024 VLDB 6.6396584e-05
5,561 ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection 2024 VLDB 6.0820916e-05
6,272 An Experimental Evaluation of Anomaly Detection in Time Series 2024 VLDB 5.8268397e-05
6,288 Multivariate Time Series Cleaning under Speed Constraints 2024 SIGMOD 5.8203148e-05
7,647 A Structured Study of Multivariate Time-Series Distance Measures 2025 SIGMOD 5.4746904e-05
7,772 OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting 2023 VLDB 5.453953e-05
8,084 Billion-Scale Bipartite Graph Embedding: A Global-Local Induced Approach 2024 VLDB 5.3917406e-05
9,572 Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains 2025 VLDB 5.154741e-05
9,575 TAB: Unified Benchmarking of Time Series Anomaly Detection Methods 2025 VLDB 5.154741e-05
10,521 The Power of Anomaly Detection in Predictive Maintenance: [Experiments & Analysis] 2026 SIGMOD 4.9769913e-05
10,581 From Suspicious Errors to Valid Data: On Repairing Spatio-Temporal Data via Spatial and Temporal Dependencies 2026 SIGMOD 4.9769913e-05
10,698 SHoTClean: Bridging Soft and Hard Constraints for Multivariate Time Series Cleaning 2026 SIGMOD 4.9769913e-05
10,879 KAFY: An Extensible and Scalable Transformers-Based System for Trajectory Data Analysis 2026 VLDB 4.9769913e-05
11,084 MS-Index: Fast Top-k Subsequence Search for Multivariate Time Series under Euclidean Distance 2026 VLDB 4.9769913e-05
11,210 The Best of Both Worlds: On Repairing Timestamps and Attribute Values for Multivariate Time Series 2025 SIGMOD 4.9769913e-05
11,257 Streaming Time Series Subsequence Anomaly Detection: A Glance and Focus Approach 2025 VLDB 4.9769913e-05
11,429 Large Language Models for Spatial Analysis Queries 2025 VLDB 4.9769913e-05
11,457 MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection 2025 VLDB 4.9769913e-05
11,600 DARKER: Efficient Transformer with Data-driven Attention Mechanism for Time Series 2024 VLDB 4.9769913e-05
Previous Page 1 / 1 Next

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.

Previous Page 1 / 1 Next

Semantically Similar Papers