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Effective imputation is a crucial preprocessing step for time series analysis.
Inference and missing data
Donald B. Rubin · 1976
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On field calibration of an electronic nose for benzene estimation in an urban pollution monitoring scenario
Saverio De Vito, Ettore Massera, Marco Piga, Luca Martinotto, and Girolamo Di Francia · 2008
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Multiparameter intelligent monitoring in intensive care ii: a public-access intensive care unit database
Mohammed Saeed, Mauricio Villarroel, Andrew T Reisner, Gari Clifford, Li-Wei Lehman, George Moody, Thomas Heldt, Tin H Kyaw, Benjamin Moody, and Roger G Mark · 2011
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mice: Multivariate imputation by chained equations in r
Stef Van Buuren and Karin Groothuis-Oudshoorn · 2011
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Predicting in-hospital mortality of icu patients: The physionet/computing in cardiology challenge 2012
Ikaro Silva, George Moody, Daniel J Scott, Leo A Celi, and Roger G Mark · 2012
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imputets: time series missing value imputation in r
Steffen Moritz and Thomas Bartz-Beielstein · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, et al · 2017
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Cautionary tales on air-quality improvement in beijing
Shuyi Zhang, Bin Guo, Anlan Dong, Jing He, Ziping Xu, and Song Xi Chen · 2017
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Brits: Bidirectional recurrent imputation for time series
Wei Cao, Dong Wang, Jian Li, Hao Zhou, Lei Li, and Yitan Li · 2018
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Multivariate time series imputation with generative adversarial networks
Yonghong Luo, Xiangrui Cai, Ying ZHANG, Jun Xu, and Yuan xiaojie · 2018
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Estimating missing data in temporal data streams using multi-directional recurrent neural networks
Jinsung Yoon, William R Zame, and Mihaela van der Schaar · 2018
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sktime: A unified interface for machine learning with time series
Markus Löning, Anthony Bagnall, Sajaysurya Ganesh, Viktor Kazakov, Jason Lines, et al · 2019
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E 2 GAN: End-to-end generative adversarial network for multivariate time series imputation
Yonghong Luo, Ying Zhang, Xiangrui Cai, and Xiaojie Yuan · 2019
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CDSA: cross-dimensional self-attention for multivariate, geo-tagged time series imputation
Jiawei Ma, Zheng Shou, Alireza Zareian, Hassan Mansour, Anthony Vetro, and Shih-Fu Chang · 2019
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Robuststl: A robust seasonal-trend decomposition algorithm for long time series
Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, and Shenghuo Zhu · 2019
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Estimating missing data in temporal data streams using multi-directional recurrent neural networks
Jinsung Yoon, William R. Zame, and Mihaela van der Schaar · 2019
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GluonTS: Probabilistic and Neural Time Series Modeling in Python
Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, et al · 2020
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Spectral temporal graph neural network for multivariate time-series forecasting
Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, et al · 2020
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Time series data imputation: A survey on deep learning approaches
Chenguang Fang and Chen Wang · 2020
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Gp-vae: Deep probabilistic time series imputation
Vincent Fortuin, Dmitry Baranchuk, Gunnar Rätsch, and Stephan Mandt · 2020
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Time series analysis
James D Hamilton · 2020
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Mind the gap: an experimental evaluation of imputation of missing values techniques in time series
Mourad Khayati, Alberto Lerner, Zakhar Tymchenko, and Philippe Cudré-Mauroux · 2020
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Early prediction of sepsis from clinical data: the physionet/computing in cardiology challenge 2019
Matthew A Reyna, Christopher S Josef, Russell Jeter, Supreeth P Shashikumar, M Brandon Westover, Shamim Nemati, Gari D Clifford, and Ashish Sharma · 2020
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Interpretable time-series classification on few-shot samples
Wensi Tang, Lu Liu, and Guodong Long · 2020
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Connecting the dots: Multivariate time series forecasting with graph neural networks
Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, and Chengqi Zhang · 2020
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Missing value imputation on multidimensional time series
Parikshit Bansal, Prathamesh Deshpande, and Sunita Sarawagi · 2021
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A knowledge distillation ensemble framework for predicting short-and long-term hospitalization outcomes from electronic health records data
Zina M Ibrahim, Daniel Bean, Thomas Searle, Linglong Qian, Honghan Wu, Anthony Shek, Zeljko Kraljevic, James Galloway, Sam Norton, James TH Teo, et al · 2021
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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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SAITS: Self-Attention-based Imputation for Time Series
Wenjie Du, David Cote, and Yan Liu · 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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Ming Jin, Huan Yee Koh, Qingsong Wen, Daniele Zambon, Cesare Alippi, Geoffrey I Webb, Irwin King, and Shirui Pan · 2023
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Probabilistic imputation for time-series classification with missing data
Seunghyun Kim, Hyunsu Kim, Eunggu Yun, Hwangrae Lee, Jaehun Lee, and Juho Lee · 2023
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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
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Neural Network Intelligence, 1 2021
Microsoft · 2021
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Uncertainty-aware variational-recurrent imputation network for clinical time series
Ahmad Wisnu Mulyadi, Eunji Jun, and Heung-Il Suk · 2021
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Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting
Kashif Rasul, Calvin Seward, Ingmar Schuster, and Roland Vollgraf · 2021
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CSDI: Conditional score-based diffusion models for probabilistic time series imputation
Yusuke Tashiro, Jiaming Song, Yang Song, and Stefano Ermon · 2021
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Mlp-mixer: An all-mlp architecture for vision
Ilya O Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, et al · 2021
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Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
Haixu Wu, Jiehui Xu, Jianmin Wang, and Mingsheng Long · 2021
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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
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Learning from data with structured missingness
Robin Mitra, Sarah F McGough, Tapabrata Chakraborti, Chris Holmes, Ryan Copping, Niels Hagenbuch, Stefanie Biedermann, Jack Noonan, Brieuc Lehmann, Aditi Shenvi, et al · 2023
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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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Non-autoregressive conditional diffusion models for time series prediction
Lifeng Shen and James Kwok · 2023
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Transformers in time series: a survey
Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, and Liang Sun · 2023
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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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Fits: Modeling time series with 10k parameters
Zhijian Xu, Ailing Zeng, and Qiang Xu · 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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Energy forecasting with robust, flexible, and explainable machine learning algorithms
Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng, Wenwei Wang, Hengbo Liu, Ziqing Ma, Xinyue Gu, et al · 2023
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Position: What can large language models tell us about time series analysis
Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, and Qingsong Wen · 2024
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Koopa: Learning non-stationary time series dynamics with koopman predictors
Yong Liu, Chenyu Li, Jianmin Wang, and Mingsheng Long · 2024
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Unveiling the secrets: How masking strategies shape time series imputation
Linglong Qian, Zina Ibrahim, Wenjie Du, Yiyuan Yang, and Richard JB Dobson · 2024
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Multi-resolution diffusion models for time series forecasting
Lifeng Shen, Weiyu Chen, and James Kwok · 2024
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Deep learning for multivariate time series imputation: A survey
Jun Wang, Wenjie Du, Wei Cao, Keli Zhang, Wenjia Wang, Yuxuan Liang, and Qingsong Wen · 2024
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A survey on diffusion models for time series and spatio-temporal data
Yiyuan Yang, Ming Jin, Haomin Wen, Chaoli Zhang, Yuxuan Liang, Lintao Ma, Yi Wang, Chenghao Liu, Bin Yang, Zenglin Xu, et al · 2024
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Frequency-domain mlps are more effective learners in time series forecasting
Kun Yi, Qi Zhang, Wei Fan, Shoujin Wang, Pengyang Wang, Hui He, Ning An, Defu Lian, Longbing Cao, and Zhendong Niu · 2024
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Self-supervised learning for time series analysis: Taxonomy, progress, and prospects
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Recurrent neural networks for multivariate time series with missing values
Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag, and Yan Liu · 2045
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