% ============================================================
% VERIFIED CITATIONS (from project references.bib)
% ============================================================

@inproceedings{vaswani2017attention,
  title={Attention is All You Need},
  author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia},
  booktitle={Advances in Neural Information Processing Systems},
  volume={30},
  year={2017}
}

@inproceedings{xu2022anomaly,
  title={Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy},
  author={Xu, Jiehui and Wu, Haixu and Wang, Jianmin and Long, Mingsheng},
  booktitle={International Conference on Learning Representations},
  year={2022}
}

@article{yang2023dcdetector,
  title={DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection},
  author={Yang, Yiyuan and Zhang, Chaoli and Zhou, Tian and Wen, Qingsong and Sun, Liang},
  journal={Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  year={2023}
}

@inproceedings{wu2023timesnet,
  title={TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis},
  author={Wu, Haixu and Hu, Tengge and Liu, Yong and Zhou, Hang and Wang, Jianmin and Long, Mingsheng},
  booktitle={International Conference on Learning Representations},
  year={2023}
}

@inproceedings{zhou2022fedformer,
  title={FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting},
  author={Zhou, Tian and Ma, Ziqing and Wen, Qingsong and Wang, Xue and Sun, Liang and Jin, Rong},
  booktitle={International Conference on Machine Learning},
  pages={27268--27286},
  year={2022},
  organization={PMLR}
}

@inproceedings{audibert2020usad,
  title={USAD: UnSupervised Anomaly Detection on Multivariate Time Series},
  author={Audibert, Julien and Michiardi, Pietro and Guyard, Fr{\'e}d{\'e}ric and Marti, S{\'e}bastien and Zuluaga, Maria A},
  booktitle={Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
  pages={3395--3404},
  year={2020}
}

@inproceedings{su2019omnianomaly,
  title={Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network},
  author={Su, Ya and Zhao, Youjian and Niu, Chenhao and Liu, Rong and Sun, Wei and Pei, Dan},
  booktitle={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
  pages={2828--2837},
  year={2019}
}

@inproceedings{chen2020simclr,
  title={A Simple Framework for Contrastive Learning of Visual Representations},
  author={Chen, Ting and Kornblith, Simon and Norber, Mohammad and Hinton, Geoffrey},
  booktitle={International Conference on Machine Learning},
  pages={1597--1607},
  year={2020},
  organization={PMLR}
}
% NOTE: Author "Norber" above may be a typo for "Norbert" -- verify before submission

% ============================================================
% ADDITIONAL CITATIONS (verified via web search, April 2026)
% BibTeX NOT fetched from DOI -- spot-check fields before submission
% ============================================================

@article{park2018multimodal,
  title={A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an {LSTM}-Based Variational Autoencoder},
  author={Park, Daehyung and Hoshi, Yuuna and Kemp, Charles C.},
  journal={IEEE Robotics and Automation Letters},
  volume={3},
  number={3},
  pages={1544--1551},
  year={2018},
  doi={10.1109/LRA.2018.2801475}
}

@article{tuli2022tranad,
  title={Tran{AD}: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data},
  author={Tuli, Shreshth and Casale, Giuliano and Jennings, Nicholas R.},
  journal={Proceedings of the VLDB Endowment},
  volume={15},
  number={6},
  pages={1201--1214},
  year={2022}
}

@inproceedings{siffer2017anomaly,
  title={Anomaly Detection in Streams with Extreme Value Theory},
  author={Siffer, Alban and Fouque, Pierre-Alain and Termier, Alexandre and Largou{\"e}t, Christine},
  booktitle={Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
  pages={1067--1075},
  year={2017},
  doi={10.1145/3097983.3098144}
}

@inproceedings{hundman2018detecting,
  title={Detecting Spacecraft Anomalies Using {LSTMs} and Nonparametric Dynamic Thresholding},
  author={Hundman, Kyle and Constantinou, Valentino and Laporte, Christopher and Colwell, Ian and Soderstrom, Tom},
  booktitle={Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
  pages={387--395},
  year={2018},
  doi={10.1145/3219819.3219845}
}

@inproceedings{mathur2016swat,
  title={{SWaT}: A Water Treatment Testbed for Research and Training on {ICS} Security},
  author={Mathur, Aditya P. and Tippenhauer, Nils Ole},
  booktitle={International Workshop on Cyber-physical Systems for Smart Water Networks},
  pages={31--36},
  year={2016}
}

@inproceedings{abdulaal2021psm,
  title={Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization},
  author={Abdulaal, Ahmed and Liu, Zhuanghua and Lancewicki, Tomer},
  booktitle={Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery \& Data Mining},
  pages={2485--2494},
  year={2021}
}

@inproceedings{kim2022towards,
  title={Towards a Rigorous Evaluation of Time-Series Anomaly Detection},
  author={Kim, Siwon and Choi, Kukjin and Choi, Hyun-Soo and Lee, Byunghan and Yoon, Sungroh},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={36},
  number={7},
  pages={7062--7070},
  year={2022}
}

@inproceedings{wu2021autoformer,
  title={Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting},
  author={Wu, Haixu and Xu, Jiehui and Wang, Jianmin and Long, Mingsheng},
  booktitle={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}