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Transformers have gained popularity in time series forecasting for their ability to capture long-sequence interactions.
Neural machine translation by jointly learning to align and translate
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Forecasting: principles and practice
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Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding. In International Conference on Learning Representations
Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting. In International Conference on Learning Representations
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A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
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Resmlp: Feedforward networks for image classification with data-efficient training
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Ts2vec: Towards universal representation of time series. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 36. 8980–8987
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Sana Tonekaboni, Danny Eytan, and Anna Goldenberg. 2021 · 2021
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Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. In Advances in Neural Information Processing Systems
Haixu Wu, Jiehui Xu, Jianmin Wang, and Mingsheng Long. 2021 · 2021
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S 2 -MLP: Spatial-Shift MLP Architecture for Vision
Tan Yu, Xu Li, Yunfeng Cai, Mingming Sun, and Ping Li. 2021 · 2021
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Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting. In The Thirty-Fifth AAAI Conference on Artificial Intelligence , Vol. 35. 11106–11115
Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, and Wancai Zhang. 2021 · 2021
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BEiT: BERT Pre-Training of Image Transformers. In International Conference on Learning Representations
Hangbo Bao, Li Dong, Songhao Piao, and Furu Wei. 2022 · 2022
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Hierarchy-guided Model Selection for Time Series Forecasting
Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, and Chandra Narayanaswami. 2022 · 2022
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Reversible Instance Normalization for Accurate Time-Series Forecasting against Distribution Shift. In International Conference on Learning Representations
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Zhihan Yue, Yujing Wang, Juanyong Duan, Tianmeng Yang, Congrui Huang, Yunhai Tong, and Bixiong Xu. 2022 · 2022
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Are Transformers Effective for Time Series Forecasting?
Ailing Zeng, Muxi Chen, Lei Zhang, and Qiang Xu. 2022a · 2022
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Github Repo: Are Transformers Effective for Time Series Forecasting?
Ailing Zeng, Muxi Chen, Lei Zhang, and Qiang Xu. 2022b · 2022
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Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures
Tianping Zhang, Yizhuo Zhang, Wei Cao, Jiang Bian, Xiaohan Yi, Shun Zheng, and Jian Li. 2022 · 2022
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FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting. In Proc. 39th International Conference on Machine Learning (Baltimore, Maryland)
Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, and Rong Jin. 2022 · 2022
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KDD 2023 Conference details
2023 · 2023
Closest in time.
Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting
Anonymous. 2023 · 2023
Closest in time.
Tsmixer: An all-mlp architecture for time series forecasting
Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan O Arik, and Tomas Pfister. 2023 · 2023
Closest in time.