Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting

Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long. Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting. In Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, A. Oh, editors, Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022. 2022. [doi]

@inproceedings{LiuWWL22-3,
  title = {Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting},
  author = {Yong Liu and Haixu Wu and Jianmin Wang and Mingsheng Long},
  year = {2022},
  url = {http://papers.nips.cc/paper_files/paper/2022/hash/4054556fcaa934b0bf76da52cf4f92cb-Abstract-Conference.html},
  researchr = {https://researchr.org/publication/LiuWWL22-3},
  cites = {0},
  citedby = {0},
  booktitle = {Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022},
  editor = {Sanmi Koyejo and S. Mohamed and A. Agarwal and Danielle Belgrave and K. Cho and A. Oh},
  isbn = {9781713871088},
}