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Transformers have achieved superior performances in many tasks in natural language processing and computer vision, which also triggered great interest in the time series community.
STL: A seasonal-trend decomposition procedure based on loess
Robert Cleveland, William Cleveland, Jean McRae, et al · 1990
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Automatic time series forecasting: the forecast package for r
Rob J Hyndman and Yeasmin Khandakar · 2008
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, et al · 2014
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N Dauphin · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, et al · 2017
Earlier work this paper cites.
Training deeper neural machine translation models with transparent attention
Ankur Bapna, Mia Xu Chen, Orhan Firat, Yuan Cao, and Yonghui Wu · 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
Earlier work this paper cites.
Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani · 2018
Earlier work this paper cites.
Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc V. Le, et al · 2019
Earlier work this paper cites.
Universal transformers
Mostafa Dehghani, Stephan Gouws, Oriol Vinyals, Jakob Uszkoreit, and Łukasz Kaiser · 2019
Earlier work this paper cites.
Neural architecture search: A survey
Elsken, Thomas, Jan Hendrik Metzen, and Frank Hutter · 2019
Earlier work this paper cites.
Deep learning for time series classification: a review
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, and Pierre-Alain Muller · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton et al · 2019
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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
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The evolved transformer
David So, Quoc Le, and Chen Liang · 2019
Earlier work this paper cites.
RobustSTL: A robust seasonal-trend decomposition algorithm for long time series
Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, et al · 2019
Earlier work this paper cites.
Modeling and applications for temporal point processes
Junchi Yan, Hongteng Xu, and Liangda Li · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, et al · 2020
Earlier work this paper cites.
Traffic transformer: Capturing the continuity and periodicity of time series for traffic forecasting
Ling Cai, Krzysztof Janowicz, Gengchen Mai, Bo Yan, and Rui Zhu · 2020
Earlier work this paper cites.
Self-attention for raw optical satellite time series classification
Marc Rußwurm and Marco Körner · 2020
Earlier work this paper cites.
MergeNAS: Merge operations into one for differentiable architecture search
Xiaoxing Wang, Chao Xue, Junchi Yan, Xiaokang Yang, Yonggang Hu, et al · 2020
Earlier work this paper cites.
Fast RobustSTL: Efficient and robust seasonal-trend decomposition for time series with complex patterns
Qingsong Wen, Zhe Zhang, Yan Li, and Liang Sun · 2020
Earlier work this paper cites.
Adversarial sparse transformer for time series forecasting
Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei, and Junzhou Huang · 2020
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Lite transformer with long-short range attention
Zhanghao Wu, Zhijian Liu, Ji Lin, Yujun Lin, and Song Han · 2020
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DeeBERT: Dynamic early exiting for accelerating bert inference
Ji Xin, Raphael Tang, Jaejun Lee, Yaoliang Yu, and Jimmy J. Lin · 2020
Earlier work this paper cites.
Spatial-temporal transformer networks for traffic flow forecasting
Mingxing Xu, Wenrui Dai, Chunmiao Liu, Xing Gao, Weiyao Lin, Guo-Jun Qi, and Hongkai Xiong · 2020
Cited alongside, same era.
Spatio-temporal graph transformer networks for pedestrian trajectory prediction
Cunjun Yu, Xiao Ma, Jiawei Ren, Haiyu Zhao, and Shuai Yi · 2020
Cited alongside, same era.
Self-supervised pretraining of transformers for satellite image time series classification
Yuan Yuan and Lei Lin · 2020
Cited alongside, same era.
Are transformers universal approximators of sequence-to-sequence functions?
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, et al · 2020
Cited alongside, same era.
Self-attentive Hawkes process
Qiang Zhang, Aldo Lipani, Omer Kirnap, and Emine Yilmaz · 2020
Cited alongside, same era.
Transformer Hawkes process
Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
Haixu Wu, Jiehui Xu, Jianmin Wang, and Mingsheng Long · 2021
Later among the works it cites.
Voice2series: Reprogramming acoustic models for time series classification
Chao-Han Huck Yang, Yun-Yun Tsai, and Pin-Yu Chen · 2021
Later among the works it cites.
A transformer-based framework for multivariate time series representation learning
George Zerveas, Srideepika Jayaraman, Dhaval Patel, Anuradha Bhamidipaty, and Carsten Eickhoff · 2021
Later among the works it cites.
Unsupervised anomaly detection in multivariate time series through transformer-based variational autoencoder
Hongwei Zhang, Yuanqing Xia, et al · 2021
Later among the works it cites.
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.
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Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, and Hongyuan Zha · 2020
Cited alongside, same era.
A review on outlier/anomaly detection in time series data
Ane Blázquez-García, Angel Conde, Usue Mori, et al · 2021
Cited alongside, same era.
Pre-trained image processing transformer
Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, et al · 2021
Cited alongside, same era.
AutoFormer: Searching transformers for visual recognition
Minghao Chen, Houwen Peng, Jianlong Fu, and Haibin Ling · 2021
Cited alongside, same era.
Learning graph structures with transformer for multivariate time series anomaly detection in IoT
Zekai Chen, Dingshuo Chen, Xiao Zhang, Zixuan Yuan, and Xiuzhen Cheng · 2021
Cited alongside, same era.
Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines
Kukjin Choi, Jihun Yi, Changhwa Park, and Sungroh Yoon · 2021
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, et al · 2021
Cited alongside, same era.
Deep learning for time series forecasting: Tutorial and literature survey
Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang, Danielle Maddix, , et al · 2022
Closest in time.
Learning to rotate: Quaternion transformer for complicated periodical time series forecasting
Weiqi Chen, Wenwei Wang, Bingqing Peng, Qingsong Wen, Tian Zhou, and Liang Sun · 2022
Closest in time.
TARNet: Task-aware reconstruction for time-series transformer
Ranak Roy Chowdhury, Xiyuan Zhang, Jingbo Shang, Rajesh K Gupta, and Dezhi Hong · 2022
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Triformer: Triangular, variable-specific attentions for long sequence multivariate time series forecasting
Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang, Tung Kieu, Xuanyi Dong, and Shirui Pan · 2022
Closest in time.
Earthformer: Exploring space-time transformers for earth system forecasting
Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Bernie Wang, Mu Li, et al · 2022
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A survey on vision transformer
Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, et al · 2022
Closest in time.
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 · 2022
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Non-stationary transformers: Exploring the stationarity in time series forecasting
Yong Liu, Haixu Wu, Jianmin Wang, and Mingsheng Long · 2022
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Transformer embeddings of irregularly spaced events and their participants
Hongyuan Mei, Chenghao Yang, and Jason Eisner · 2022
Closest in time.
Efficient transformers: A survey
Yi Tay, Mostafa Dehghani, Dara Bahri, and Donald Metzler · 2022
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TranAD: Deep transformer networks for anomaly detection in multivariate time series data
Shreshth Tuli, Giuliano Casale, and Nicholas R Jennings · 2022
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Variational transformer-based anomaly detection approach for multivariate time series
Xixuan Wang, Dechang Pi, Xiangyan Zhang, et al · 2022
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Robust time series analysis and applications: An industrial perspective
Qingsong Wen, Linxiao Yang, Tian Zhou, and Liang Sun · 2022
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Anomaly Transformer: Time series anomaly detection with association discrepancy
Jiehui Xu, Haixu Wu, Jianmin Wang, and Mingsheng Long · 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.
AirFormer: Predicting nationwide air quality in china with transformers
Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, and Roger Zimmermann · 2023
Closest in time.
A time series is worth 64 words: Long-term forecasting with transformers
Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam · 2023
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Scaleformer: iterative multi-scale refining transformers for time series forecasting
Amin Shabani, Amir Abdi, Lili Meng, and Tristan Sylvain · 2023
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Are transformers effective for time series forecasting?
Ailing Zeng, Muxi Chen, Lei Zhang, and Qiang Xu · 2023
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Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting
Yunhao Zhang and Junchi Yan · 2023
Closest in time.