1. Vaswani, A., et al.: Attention is all you need. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, pp. 6000–6010. Curran Associates Inc. (2017)
2. Zhou, H., Zhang, S., Peng, J., et al.: Informer: beyond efficient transformer for long sequence time-series forecasting. In: Proceedings of the 35th AAAI Conference on Artificial Intelligence, vol. 35, no. 12, pp. 11106–11115. Association for the Advancement of Artificial Intelligence (AAAI) (2021)
3. Wu, H., Xu, J., Wang, J., et al.: Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting. Adv. Neural. Inf. Process. Syst. 34(1), 22419–22430 (2021)
4. Durbin, J., Koopman, S.J.: Time Series Analysis by State Space Methods: Second Edition. Oxford University Press (2012). https://doi.org/10.1093/acprof:oso/9780199641178.001.0001
5. Pascanu, R., Mikolov, T., Bengio, Y.: On the difficulty of training recurrent neural networks. In: 30th International Conference on Machine Learning, pp. 1310–1318. Association for Computing and Machinery (ACM) (2013)