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Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task.
Exponential smoothing: The state of the art
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Greedy function approximation: a gradient boosting machine
Jerome H Friedman · 2001
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Direct multi-step estimation and forecasting
Guillaume Chevillon · 2007
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Ruijun Dong and Witold Pedrycz · 2008
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Stock price prediction using the arima model
Adebiyi A Ariyo, Adewumi O Adewumi, and Charles K Ayo · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Modeling long- and short-term temporal patterns with deep neural networks
Guokun Lai, Wei-Cheng Chang, Yiming Yang, and Hanxiao Liu · 2017
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Deepar: Probabilistic forecasting with autoregressive recurrent networks
David Salinas, Valentin Flunkert, and Jan Gasthaus · 2017
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Forecasting at scale
Sean J. Taylor and Benjamin Letham · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
Shaojie Bai, J Zico Kolter, and Vladlen Koltun · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Speech-transformer: a no-recurrence sequence-to-sequence model for speech recognition
Linhao Dong, Shuang Xu, and Bo Xu · 2018
Cited alongside, same era.
Time series is a special sequence: Forecasting with sample convolution and interaction
Minhao Liu, Ailing Zeng, Zhijian Xu, Qiuxia Lai, and Qiang Xu · 2021
Later among the works it cites.
Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting
Shizhan Liu, Hang Yu, Cong Liao, Jianguo Li, Weiyao Lin, Alex X Liu, and Schahram Dustdar · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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T-wavenet: A tree-structured wavelet neural network for time series signal analysis
LIU Minhao, Ailing Zeng, LAI Qiuxia, Ruiyuan Gao, Min Li, Jing Qin, and Qiang Xu · 2021
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Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
Jiehui Xu, Jianmin Wang, Mingsheng Long, et al · 2021
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Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting
Shiyang Li, Xiaoyong Jin, Yao Xuan, Xiyou Zhou, Wenhu Chen, Yu-Xiang Wang, and Xifeng Yan · 2019
Cited alongside, same era.
Recurrent neural networks for time series forecasting
Gábor Petneházi · 2019
Cited alongside, same era.
Time series analysis
James Douglas Hamilton · 2020
Cited alongside, same era.
An evaluation of change point detection algorithms
Gerrit JJ van den Burg and Christopher KI Williams · 2020
Cited alongside, same era.
Do we really need deep learning models for time series forecasting?
Shereen Elsayed, Daniela Thyssens, Ahmed Rashed, Hadi Samer Jomaa, and Lars Schmidt-Thieme · 2021
Cited alongside, same era.
Informer: Beyond efficient transformer for long sequence time-series forecasting
Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, and Wancai Zhang · 2021
Later among the works it cites.
Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang, Tung Kieu, Xuanyi Dong, and Shirui Pan · 2022
Closest in time.
Transformers in time series: A survey
Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, and Liang Sun · 2022
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Deciwatch: A simple baseline for 10x efficient 2d and 3d pose estimation
Ailing Zeng, Xuan Ju, Lei Yang, Ruiyuan Gao, Xizhou Zhu, Bo Dai, and Qiang Xu · 2022
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Fedformer: Frequency enhanced decomposed transformer for long-term series forecasting
Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, and Rong Jin · 2022
Closest in time.