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Transformer-based methods have shown great potential in long-term time series forecasting.
Recurrent networks and narma modeling
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Support vector machine with adaptive parameters in financial time series forecasting
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Wavenet: A generative model for raw audio
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Conditional time series forecasting with convolutional neural networks
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A dual-stage attention-based recurrent neural network for time series prediction
Qin, Y., Song, D., Chen, H., Cheng, W., Jiang, G., and Cottrell, G · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
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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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Modeling long-and short-term temporal patterns with deep neural networks
Lai, G., Chang, W.-C., Yang, Y., and Liu, H · 2018
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N-beats: Neural basis expansion analysis for interpretable time series forecasting
Oreshkin, B. N., Carpov, D., Chapados, N., and Bengio, Y · 2019
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Pytorch: An imperative style, high-performance deep learning library
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Think globally, act locally: A deep neural network approach to high-dimensional time series forecasting
Sen, R., Yu, H.-F., and Dhillon, I · 2019
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End-to-end object detection with transformers
Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., and Zagoruyko, S · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
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Attend and diagnose: Clinical time series analysis using attention models
Song, H., Rajan, D., Thiagarajan, J. J., and Spanias, A · 2018
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Forecasting at scale
Taylor, S. J. and Letham, B · 2018
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Reformer: The efficient transformer
Kitaev, N., Kaiser, L., and Levskaya, A · 2019
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Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting
Li, S., Jin, X., Xuan, Y., Zhou, X., Chen, W., Wang, Y.-X., and Yan, X · 2019
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Deepar: Probabilistic forecasting with autoregressive recurrent networks
Salinas, D., Flunkert, V., Gasthaus, J., and Januschowski, T · 2020
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Deep transformer models for time series forecasting: The influenza prevalence case
Wu, N., Green, B., Ben, X., and O’Banion, S · 2020
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Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
Wu, H., Xu, J., Wang, J., and Long, M · 2021
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Informer: Beyond efficient transformer for long sequence time-series forecasting
Zhou, H., Zhang, S., Peng, J., Zhang, S., Li, J., Xiong, H., and Zhang, W · 2021
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