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Time series are widely used as signals in many classification/regression tasks.
On the estimation of arima models with missing values
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Dynammo: Mining and summarization of coevolving sequences with missing values
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An agent-based approach to care in independent living
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The effects of the irregular sample and missing data in time series analysis
D. M. Kreindler and C. J. Lumsden · 2012
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Recent techniques of clustering of time series data: a survey
S. Rani and G. Sikka · 2012
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Predicting in-hospital mortality of icu patients: The physionet/computing in cardiology challenge 2012
I. Silva, G. Moody, D. J. Scott, L. A. Celi, and R. G. Mark · 2012
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Training energy-based models for time-series imputation
P. Brakel, D. Stroobandt, and B. Schrauwen · 2013
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On the difficulty of training recurrent neural networks
R. Pascanu, T. Mikolov, and Y. Bengio · 2013
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D. Sussillo and O. Barak · 2013
Doctor ai: Predicting clinical events via recurrent neural networks
E. Choi, M. T. Bahadori, A. Schuetz, W. F. Stewart, and J. Sun · 2016
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Deep learning
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Directly modeling missing data in sequences with rnns: Improved classification of clinical time series
Z. C. Lipton, D. Kale, and R. Wetzel · 2016
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Learning linear dynamical systems from multivariate time series: A matrix factorization based framework
Z. Liu and M. Hauskrecht · 2016
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St-mvl: filling missing values in geo-sensory time series data
X. Yi, Y. Zheng, J. Zhang, and T. Li · 2016
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Temporal regularized matrix factorization for high-dimensional time series prediction
H.-F. Yu, N. Rao, and I. S. Dhillon · 2016
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
K. Cho, B. Van Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio · 2014
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Deep learning for multivariate financial time series, 2015
B. Batres-Estrada · 2015
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Scheduled sampling for sequence prediction with recurrent neural networks
S. Bengio, O. Vinyals, N. Jaitly, and N. Shazeer · 2015
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Bidirectional recurrent neural networks as generative models
M. Berglund, T. Raiko, M. Honkala, L. Kärkkäinen, A. Vetek, and J. T. Karhunen · 2015
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Convolutional lstm network: A machine learning approach for precipitation nowcasting
S. Xingjian, Z. Chen, H. Wang, D.-Y. Yeung, W.-K. Wong, and W.-c. Woo · 2015
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The arrow of time in multivariate time series
S. Bauer, B. Schölkopf, and J. Peters · 2016
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imputeTS: Time Series Missing Value Imputation in R
S. Moritz and T. Bartz-Beielstein · 2017
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Deepsd: supply-demand prediction for online car-hailing services using deep neural networks
D. Wang, W. Cao, J. Li, and J. Ye · 2017
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Multi-directional recurrent neural networks: A novel method for estimating missing data
J. Yoon, W. R. Zame, and M. van der Schaar · 2017
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Deep spatio-temporal residual networks for citywide crowd flows prediction
J. Zhang, Y. Zheng, and D. Qi · 2017
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Recurrent neural networks for multivariate time series with missing values
Z. Che, S. Purushotham, K. Cho, D. Sontag, and Y. Liu · 2018
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