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Time series analysis plays a critical role in numerous applications, supporting tasks such as forecasting, classification, anomaly detection, and imputation.
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Ami Harti · 1993
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Freeway performance measurement system: Mining loop detector data
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Xgboost: A scalable tree boosting system
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Attention is all you need
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Lstm network: a deep learning approach for short-term traffic forecast
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The uea multivariate time series classification archive, 2018
Anthony Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn, James Large, Aaron Bostrom, Paul Southam, and Eamonn Keogh · 2018
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Detecting spacecraft anomalies using lstms and nonparametric dynamic thresholding
Kyle Hundman, Valentino Constantinou, Christopher Laporte, Ian Colwell, and Tom Soderstrom · 2018
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The m4 competition: Results, findings, conclusion and way forward
Spyros Makridakis, Evangelos Spiliotis, and Vassilios Assimakopoulos · 2018
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Unsupervised scalable representation learning for multivariate time series
Jean-Yves Franceschi, Aymeric Dieuleveut, and Martin Jaggi · 2019
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Similarity of neural network representations revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey Hinton · 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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N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
Boris N Oreshkin, Dmitri Carpov, Nicolas Chapados, and Yoshua Bengio · 2019
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Pytorch: An imperative style, high-performance deep learning library
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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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Accurate medium-range global weather forecasting with 3d neural networks
Kaifeng Bi, Lingxi Xie, Hengheng Zhang, Xin Chen, Xiaotao Gu, and Qi Tian · 2023
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Tsmixer: Lightweight mlp-mixer model for multivariate time series forecasting
Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam · 2023
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Large language models are zero-shot time series forecasters
Nate Gruver, Marc Anton Finzi, Shikai Qiu, and Andrew Gordon Wilson · 2023
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Robust anomaly detection for multivariate time series through stochastic recurrent neural network
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Rocket: exceptionally fast and accurate time series classification using random convolutional kernels
Angus Dempster, Franccois Petitjean, and Geoffrey I. Webb · 2020
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Reformer: The efficient transformer
Nikita Kitaev, Lukasz Kaiser, and Anselm Levskaya · 2020
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Personalized imputation on wearable-sensory time series via knowledge transfer
Xian Wu, Stephen Mattingly, Shayan Mirjafari, Chao Huang, and Nitesh V Chawla · 2020
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Practical approach to asynchronous multivariate time series anomaly detection and localization
Ahmed Abdulaal, Zhuanghua Liu, and Tomer Lancewicki · 2021
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Clocs: Contrastive learning of cardiac signals across space, time, and patients
Dani Kiyasseh, Tingting Zhu, and David A Clifton · 2021
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Autoformer: Decomposition transformers with Auto-Correlation for long-term series forecasting
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Yong Liu, Chenyu Li, Jianmin Wang, and Mingsheng Long · 2023
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Tfdnet: Time-frequency enhanced decomposed network for long-term time series forecasting
Yuxiao Luo, Ziyu Lyu, and Xingyu Huang · 2023
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A time series is worth 64 words: Long-term forecasting with transformers
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TimesNet: Temporal 2d-variation modeling for general time series analysis
Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, and Mingsheng Long · 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
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One fits all: Power general time series analysis by pretrained lm
Tian Zhou, Peisong Niu, Liang Sun, Rong Jin, et al · 2023
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itransformer: Inverted transformers are effective for time series forecasting
Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, and Mingsheng Long · 2024
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