% Selected decomposition literature. Verified 2026-10-29.
% Normalized from DBLP metadata where available and primary publication records.
% Stable local keys; optional unverified fields omitted. These are not unmodified provider exports.
% Publication years refer to the cited version; arXiv identifiers may refer to earlier preprints.

% Metadata source: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/stl-a-seasonal-trend-decomposition-procedure-based-on-loess.pdf
@article{cleveland1990stl,
  title = {{STL: A Seasonal-Trend Decomposition Procedure Based on Loess}},
  author = {Robert B. Cleveland and William S. Cleveland and Jean E. McRae and Irma Terpenning},
  journal = {Journal of Official Statistics},
  year = {1990},
  volume = {6},
  number = {1},
  pages = {3--73},
  note = {The publisher PDF gives pages 3--73, including discussion.},
  url = {https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/stl-a-seasonal-trend-decomposition-procedure-based-on-loess.pdf},
  urldate = {2026-10-29},
}

% Metadata source: https://link.springer.com/book/10.1007/978-3-662-62436-4
@book{golyandina2020ssa,
  title = {{Singular Spectrum Analysis for Time Series}},
  author = {Nina Golyandina and Anatoly Zhigljavsky},
  publisher = {Springer},
  year = {2020},
  edition = {2},
  series = {SpringerBriefs in Statistics},
  doi = {10.1007/978-3-662-62436-4},
  url = {https://link.springer.com/book/10.1007/978-3-662-62436-4},
  urldate = {2026-10-29},
}

% Metadata source: https://doi.org/10.1098/rspa.1998.0193
@article{huang1998emd,
  title = {{The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis}},
  author = {Norden E. Huang and Zheng Shen and Steven R. Long and Manli C. Wu and Hsing H. Shih and Quanan Zheng and Nai-Chyuan Yen and Chi Chao Tung and Henry H. Liu},
  journal = {Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences},
  year = {1998},
  volume = {454},
  number = {1971},
  pages = {903--995},
  doi = {10.1098/rspa.1998.0193},
  url = {https://doi.org/10.1098/rspa.1998.0193},
  urldate = {2026-10-29},
}

% Metadata source: https://doi.org/10.1142/S1793536909000047
@article{wu2009eemd,
  title = {{Ensemble Empirical Mode Decomposition: A Noise-Assisted Data Analysis Method}},
  author = {Zhaohua Wu and Norden E. Huang},
  journal = {Advances in Adaptive Data Analysis},
  year = {2009},
  volume = {1},
  number = {1},
  pages = {1--41},
  doi = {10.1142/S1793536909000047},
  url = {https://doi.org/10.1142/S1793536909000047},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.uni-trier.de/rec/conf/icassp/TorresCSF11.html ; https://sinc.unl.edu.ar/sinc-publications/2011/TCSF11/
@inproceedings{torres2011ceemdan,
  title = {{A complete ensemble empirical mode decomposition with adaptive noise}},
  author = {María Eugenia Torres and Marcelo Alejandro Colominas and Gastón Schlotthauer and Patrick Flandrin},
  booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing},
  year = {2011},
  pages = {4144--4147},
  publisher = {IEEE},
  doi = {10.1109/ICASSP.2011.5947265},
  url = {https://sinc.unl.edu.ar/sinc-publications/2011/TCSF11/},
  bibsource = {https://dblp.uni-trier.de/rec/conf/icassp/TorresCSF11.html},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.org/rec/journals/tsp/DragomiretskiyZ14 ; https://doi.org/10.1109/TSP.2013.2288675
@article{dragomiretskiy2014vmd,
  title = {{Variational Mode Decomposition}},
  author = {Konstantin Dragomiretskiy and Dominique Zosso},
  journal = {IEEE Transactions on Signal Processing},
  year = {2014},
  volume = {62},
  number = {3},
  pages = {531--544},
  doi = {10.1109/TSP.2013.2288675},
  url = {https://doi.org/10.1109/TSP.2013.2288675},
  bibsource = {https://dblp.org/rec/journals/tsp/DragomiretskiyZ14},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.org/rec/journals/pami/Mallat89 ; https://doi.org/10.1109/34.192463
@article{mallat1989wavelet,
  title = {{A Theory for Multiresolution Signal Decomposition: The Wavelet Representation}},
  author = {Stéphane Mallat},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1989},
  volume = {11},
  number = {7},
  pages = {674--693},
  doi = {10.1109/34.192463},
  url = {https://doi.org/10.1109/34.192463},
  bibsource = {https://dblp.org/rec/journals/pami/Mallat89},
  urldate = {2026-10-29},
}

% Metadata source: https://www.inderscience.com/info/e_inarticle.php?artid=143957
@article{bandara2025mstl,
  title = {{MSTL: a seasonal-trend decomposition algorithm for time series with multiple seasonal patterns}},
  author = {Kasun Bandara and Rob J. Hyndman and Christoph Bergmeir},
  journal = {International Journal of Operational Research},
  year = {2025},
  volume = {52},
  number = {1},
  pages = {79--98},
  doi = {10.1504/IJOR.2025.143957},
  eprint = {2107.13462},
  archivePrefix = {arXiv},
  url = {https://www.inderscience.com/info/e_inarticle.php?artid=143957},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.org/rec/conf/nips/WuXWL21.html ; https://proceedings.neurips.cc/paper_files/paper/2021/hash/bcc0d400288793e8bdcd7c19a8ac0c2b-Abstract.html
@inproceedings{wu2021autoformer,
  title = {{Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting}},
  author = {Haixu Wu and Jiehui Xu and Jianmin Wang and Mingsheng Long},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2021},
  volume = {34},
  pages = {22419--22430},
  eprint = {2106.13008},
  archivePrefix = {arXiv},
  url = {https://proceedings.neurips.cc/paper_files/paper/2021/hash/bcc0d400288793e8bdcd7c19a8ac0c2b-Abstract.html},
  bibsource = {https://dblp.org/rec/conf/nips/WuXWL21.html},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.org/rec/conf/aaai/ZengCZ023.html ; https://ojs.aaai.org/index.php/AAAI/article/view/26317
@inproceedings{zeng2023dlinear,
  title = {{Are Transformers Effective for Time Series Forecasting?}},
  author = {Ailing Zeng and Muxi Chen and Lei Zhang and Qiang Xu},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  year = {2023},
  volume = {37},
  number = {9},
  pages = {11121--11128},
  doi = {10.1609/aaai.v37i9.26317},
  eprint = {2205.13504},
  archivePrefix = {arXiv},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26317},
  bibsource = {https://dblp.org/rec/conf/aaai/ZengCZ023.html},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.org/rec/conf/iclr/WangWSHLMZ024.html ; https://proceedings.iclr.cc/paper_files/paper/2024/hash/a7ac8a21e5a27e7ab31a5f42a0117bdb-Abstract-Conference.html
@inproceedings{wang2024timemixer,
  title = {{TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting}},
  author = {Shiyu Wang and Haixu Wu and Xiaoming Shi and Tengge Hu and Huakun Luo and Lintao Ma and James Y. Zhang and Jun Zhou},
  booktitle = {International Conference on Learning Representations},
  year = {2024},
  eprint = {2405.14616},
  archivePrefix = {arXiv},
  url = {https://proceedings.iclr.cc/paper_files/paper/2024/hash/a7ac8a21e5a27e7ab31a5f42a0117bdb-Abstract-Conference.html},
  bibsource = {https://dblp.org/rec/conf/iclr/WangWSHLMZ024.html},
  urldate = {2026-10-29},
}

% Metadata source: https://proceedings.iclr.cc/paper_files/paper/2025/hash/2b187165e28fdfdc0ffb34d1bfff2b0c-Abstract-Conference.html
@inproceedings{wang2025timemixerpp,
  title = {{TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis}},
  author = {Shiyu Wang and Jiawei Li and Xiaoming Shi and Zhou Ye and Baichuan Mo and Wenze Lin and Shengtong Ju and Zhixuan Chu and Ming Jin},
  booktitle = {International Conference on Learning Representations},
  year = {2025},
  eprint = {2410.16032},
  archivePrefix = {arXiv},
  url = {https://proceedings.iclr.cc/paper_files/paper/2025/hash/2b187165e28fdfdc0ffb34d1bfff2b0c-Abstract-Conference.html},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.org/rec/conf/icml/MasseranoAHZFMW25 ; https://proceedings.mlr.press/v267/masserano25a.html
@inproceedings{masserano2025wavetoken,
  title = {{Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization}},
  author = {Luca Masserano and Abdul Fatir Ansari and Boran Han and Xiyuan Zhang and Christos Faloutsos and Michael W. Mahoney and Andrew Gordon Wilson and Youngsuk Park and Syama Sundar Rangapuram and Danielle C. Maddix and Bernie Wang},
  booktitle = {Proceedings of the 42nd International Conference on Machine Learning},
  year = {2025},
  volume = {267},
  series = {Proceedings of Machine Learning Research},
  pages = {43248--43275},
  publisher = {PMLR},
  eprint = {2412.05244},
  archivePrefix = {arXiv},
  url = {https://proceedings.mlr.press/v267/masserano25a.html},
  bibsource = {https://dblp.org/rec/conf/icml/MasseranoAHZFMW25},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.org/rec/conf/nips/QiuWCLGHY25.html ; https://proceedings.neurips.cc/paper_files/paper/2025/hash/2823c4f838727564c108c85d7e6e8507-Abstract-Conference.html
@inproceedings{qiu2025dbloss,
  title = {{DBLoss: Decomposition-based Loss Function for Time Series Forecasting}},
  author = {Xiangfei Qiu and Xingjian Wu and Hanyin Cheng and Xvyuan Liu and Chenjuan Guo and Jilin Hu and Bin Yang},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2025},
  volume = {38},
  doi = {10.52202/085713-0936},
  url = {https://proceedings.neurips.cc/paper_files/paper/2025/hash/2823c4f838727564c108c85d7e6e8507-Abstract-Conference.html},
  bibsource = {https://dblp.org/rec/conf/nips/QiuWCLGHY25.html},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.uni-trier.de/rec/conf/nips/LuoW25.html ; https://proceedings.nips.cc/paper_files/paper/2025/hash/2e56189f02f4b00de8bf6020455830e0-Abstract-Conference.html
@inproceedings{luo2025decompnet,
  title = {{DecompNet: Enhancing Time Series Forecasting Models with Implicit Decomposition}},
  author = {Donghao Luo and Xue Wang},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2025},
  volume = {38},
  doi = {10.52202/085713-1083},
  url = {https://proceedings.nips.cc/paper_files/paper/2025/hash/2e56189f02f4b00de8bf6020455830e0-Abstract-Conference.html},
  bibsource = {https://dblp.uni-trier.de/rec/conf/nips/LuoW25.html},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.dagstuhl.de/rec/conf/nips/LiLWLPLGZG25.html ; https://papers.neurips.cc/paper_files/paper/2025/hash/0e82ef0c89df6a6eff8734ea7e27c42f-Abstract-Conference.html
@inproceedings{li2025implicit,
  title = {{Towards Accurate Time Series Forecasting via Implicit Decoding}},
  author = {Xinyu Li and Yuchen Luo and Hao Wang and Haoxuan Li and Liuhua Peng and Feng Liu and Yandong Guo and Kun Zhang and Mingming Gong},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2025},
  volume = {38},
  doi = {10.52202/085713-0337},
  url = {https://papers.neurips.cc/paper_files/paper/2025/hash/0e82ef0c89df6a6eff8734ea7e27c42f-Abstract-Conference.html},
  bibsource = {https://dblp.dagstuhl.de/rec/conf/nips/LiLWLPLGZG25.html},
  urldate = {2026-10-29},
}

% Metadata source: https://dblp.org/rec/journals/sigpro/JiaCLCSKGBDS26.html ; https://www.sciencedirect.com/science/article/pii/S0165168425003172
@article{jia2026stvmd,
  title = {{Short-time variational mode decomposition}},
  author = {Hao Jia and Pengfei Cao and Tong Liang and Cesar F. Caiafa and Zhe Sun and Yasuhiro Kushihashi and Antoni Grau and Yolanda Bolea and Feng Duan and Jordi Solé-Casals},
  journal = {Signal Processing},
  year = {2026},
  volume = {238},
  pages = {110203},
  doi = {10.1016/j.sigpro.2025.110203},
  eprint = {2501.09174},
  archivePrefix = {arXiv},
  url = {https://www.sciencedirect.com/science/article/pii/S0165168425003172},
  bibsource = {https://dblp.org/rec/journals/sigpro/JiaCLCSKGBDS26.html},
  urldate = {2026-10-29},
}

% Metadata source: https://link.springer.com/article/10.1007/s10463-026-00987-8
@article{movahedifar2026grouping,
  title = {{Confident grouping in singular spectrum analysis via multiple testing}},
  author = {Maryam Movahedifar and Friederike Preusse and Anna Vesely and Thorsten Dickhaus},
  journal = {Annals of the Institute of Statistical Mathematics},
  year = {2026},
  note = {Published online 25 June 2026; volume and page numbers were not shown in the checked record.},
  doi = {10.1007/s10463-026-00987-8},
  url = {https://link.springer.com/article/10.1007/s10463-026-00987-8},
  urldate = {2026-10-29},
}

% Metadata source: https://proceedings.iclr.cc/paper_files/paper/2026/hash/f46ddea413df86832418c5e04e59644f-Abstract-Conference.html
@inproceedings{zhao2026timerecipe,
  title = {{TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness}},
  author = {Zhiyuan Zhao and Juntong Ni and Shangqing Xu and Haoxin Liu and Wei Jin and B. Aditya Prakash},
  booktitle = {International Conference on Learning Representations},
  year = {2026},
  url = {https://proceedings.iclr.cc/paper_files/paper/2026/hash/f46ddea413df86832418c5e04e59644f-Abstract-Conference.html},
  urldate = {2026-10-29},
}

% Metadata source: https://proceedings.mlr.press/v306/wu26bh.html
@inproceedings{wu2026standalone,
  title = {{Time-Series Decomposition as a Standalone Task: A Mechanism-Driven Diagnostic Benchmark}},
  author = {Zipeng Wu and Jiani Wei and Shiqiao Zhou and Jiajun Chen and Fabian Spill and J. W. Andrews},
  booktitle = {Proceedings of the 43rd International Conference on Machine Learning},
  year = {2026},
  volume = {306},
  series = {Proceedings of Machine Learning Research},
  pages = {137063--137084},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v306/wu26bh.html},
  urldate = {2026-10-29},
}