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Time series constitute a challenging data type for machine learning algorithms, due to their highly variable lengths and sparse labeling in practice.
Long short-term memory
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Distributed representations of words and phrases and their compositionality
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Kingma, D. P. and Ba, J · 2015
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The BOSS is concerned with time series classification in the presence of noise
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Facenet: A unified embedding for face recognition and clustering
Schroff, F., Kalenichenko, D., and Philbin, J · 2015
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Unsupervised learning of video representations using LSTMs
Srivastava, N., Mansimov, E., and Salakhudinov, R · 2015
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Multi-scale convolutional neural networks for time series classification
Cui, Z., Chen, W., and Chen, Y · 2016
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Deep Learning
Goodfellow, I., Bengio, Y., and Courville, A · 2016
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Hyvarinen, A. and Morioka, H · 2016
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Weight normalization: A simple reparameterization to accelerate training of deep neural networks
Salimans, T. and Kingma, D. P · 2016
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Multi-scale context aggregation by dilated convolutions
Yu, F. and Koltun, V · 2016
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Time series classification from scratch with deep neural networks: A strong baseline
Wang, Z., Yan, W., and Oates, T · 2017
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The UEA multivariate time series classification archive, 2018
Bagnall, A., Dau, H. A., Lines, J., Flynn, M., Large, J., Bostrom, A., Southam, P., and Keogh, E · 2018
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An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
Bai, S., Kolter, J. Z., and Koltun, V · 2018
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The UCR time series classification archive, October 2018
Dau, H. A., Keogh, E., Kamgar, K., Yeh, C.-C. M., Zhu, Y., Gharghabi, S., Ratanamahatana, C. A., Yanping, Hu, B., Begum, N., Bagnall, A., Mueen, A., and Batista, G · 2018
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Unsupervised learning of semantic audio representations
Jansen, A., Plakal, M., Pandya, R., Ellis, D. P. W., Hershey, S., Liu, J., Moore, R. C., and Saurous, R. A · 2018
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Recent trends in deep learning based natural language processing
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A theoretical analysis of contrastive unsupervised representation learning
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