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Time series prediction has been studied in a variety of domains.
Hypothesis Testing in Time Series Anal- ysis
P. Whittle · 1951
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Digital processing of speech signals
L. Rabiner and R. Schafer · 1978
Earlier work this paper cites.
Learning representations by back-propagating errors
D. E. Rumelhart, G. E. Hinton, and R. J. Williams · 1988
Earlier work this paper cites.
Distributed representations, simple recurrent networks, and grammatical structure
J. L. Elman · 1991
Earlier work this paper cites.
Learning long-term dependencies with gradient descent is difficult
Y. Bengio, P. Simard, and P. Frasconi · 1994
Earlier work this paper cites.
Recurrent neural networks and robust time series prediction
J. T. Connor, R. D. Martin, and L. E. Atlas · 1994
Earlier work this paper cites.
Convolutional networks for images, speech, and time series
Y. LeCun and Y. Bengio · 1995
Earlier work this paper cites.
Learning long-term dependencies in narx recurrent neural networks
T. Lin, B. Horne, P. Tino, and C. Giles · 1996
Earlier work this paper cites.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Financial time series prediction using least squares support vector machines within the evidence framework
T. Van Gestel, J. Suykens, D. Baestaens, A. Lambrechts, G. Lanckriet, B. Vandaele, B. De Moor, and J. Vandewalle · 2001
Earlier work this paper cites.
Denoising nonlinear time series by adaptive filtering and wavelet shrinkage: a comparison
J. Gao, H. Sultan, J. Hu, and W.-W. Tung · 2010
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Generating text with recurrent neural networks
I. Sutskever, J. Martens, and G. E. Hinton · 2011
Cited alongside, same era.
Exploring convolutional neural network structures and optimization techniques for speech recognition
O. Abdel-Hamid, L. Deng, and D. Yu · 2013
Cited alongside, same era.
Improving deep neural networks for lvcsr using rectified linear units and dropout
G. E. Dahl, T. N. Sainath, and G. E. Hinton · 2013
Cited alongside, same era.
Speech recognition with deep recurrent neural networks
A. Graves, A.-r. Mohamed, and G. E. Hinton · 2013
Cited alongside, same era.
Dynamic covariance models for multivariate financial time series
Y. Wu, J. M. Hernández-Lobato, and Z. Ghahramani · 2013
Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Deep recurrent neural networks for time series prediction
S. C. Prasad and P. Prasad · 2014
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Learning representations from eeg with deep recurrent-convolutional neural networks
P. Bashivan, I. Rish, M. Yeasin, and N. Codella · 2015
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A regularized linear dynamical system framework for multivariate time series analysis
Z. Liu and M. Hauskrecht · 2015
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Convolutional lstm network: A machine learning approach for precipitation nowcasting
X. Shi, Z. Chen, H. Wang, D.-Y. Yeung, W.-K. Wong, and W.-c. Woo · 2015
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Neural machine translation by jointly learning to align and translate
D. Bahdanau, K. Cho, and Y. Bengio · 2014
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On the properties of neural machine translation: Encoder-decoder approaches
K. Cho, B. V. Merriënboer, D. Bahdanau, and Y. Bengio · 2014
Cited alongside, same era.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
K. Cho, B. V. Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio · 2014
Cited alongside, same era.
Empirical evaluation of gated recurrent neural networks on sequence modeling
J. Chung, C. Gulcehre, K. Cho, and Y. Bengio · 2014
Cited alongside, same era.
J. G. Zilly, R. K. Srivastava, J. Koutník, and J. Schmidhuber · 2016
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Revisiting narx recurrent neural networks for long-term dependencies
R. DiPietro, N. Navab, and G. D. Hager · 2017
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Prediction under uncertainty in sparse spectrum gaussian processes with applications to filtering and control
Y. Pan, X. Yan, E. A. Theodorou, and B. Boots · 2017
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A dual-stage attention-based recurrent neural network for time series prediction
Y. Qin, D. Song, H. Cheng, W. Cheng, G. Jiang, and G. Cottrell · 2017
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Inception-v4, inception-resnet and the impact of residual connections on learning
C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi · 2017
Later among the works it cites.