[18] Salah El Hihi and Yoshua Bengio. 1995. Hierarchical Recurrent Neural Networks for Long-Term Dependencies. Advances in Neural Information Processing Systems 8 (1995).
[19] Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, and Yuyang Wang. 2019. Forecasting Big Time Series: Theory and Practice. In ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 3209-3210.
[20] Chenyou Fan, Yuze Zhang, Yi Pan, Xiaoyue Li, Chi Zhang, Rong Yuan, Di Wu, Wensheng Wang, Jian Pei, and Heng Huang. 2019. Multi-Horizon Time Series Forecasting with Temporal Attention Learning. In ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2527-2535.
[21] Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, and Tim Januschowski. 2019. Probabilistic Forecasting with Spline Quantile Function RNNs. In International Conference on Artificial Intelligence and Statistics. 1901-1910.
[22] Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford. 2021. Datasheets for Datasets. Commun. ACM 64, 12 (2021), 86-92.
[23] Mathieu Germain, Karol Gregor, Iain Murray, and Hugo Larochelle. 2015. MADE: Masked Autoencoder for Distribution Estimation. In International Conference on Machine Learning. 881-889.
[24] Tilmann Gneiting and Adrian E Raftery. 2007. Strictly Proper Scoring Rules, Prediction, and Estimation. J. Amer. Statist. Assoc. 102, 477 (2007), 359-378.
[25] Hila Gonen and Yoav Goldberg. 2019. Lipstick on a pig: Debiasing methods cover up systematic gender biases in word embeddings but do not remove them. arXiv preprint arXiv:1903.03862 (2019).
[26] Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative Adversarial Nets. Advances in Neural Information Processing Systems (2014), 2672–2680.
[27] Adele Gouttes, Kashif Rasul, Mateusz Koren, Johannes Stephan, and Tofigh Naghibi. 2021. Probabilistic Time Series Forecasting with Implicit Quantile Networks. arXiv preprint arXiv:2107.03743 (2021).
[28] Alex Graves. 2013. Generating Sequences with Recurrent Neural Networks. arXiv preprint arXiv:1308.0850 (2013).
[29] Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton. 2013. Speech Recognition with Deep Recurrent Neural Networks. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. 6645–6649.
[30] Alex Graves and Jürgen Schmidhuber. 2008. Offline handwriting recognition with multidimensional recurrent neural networks. Advances in Neural Information Processing Systems 21 (2008).
[31] Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In IEEE Conference on Computer Vision and Pattern Recognition. 770-778.
[32] Hansika Hewamalage, Klaus Ackermann, and Christoph Bergmeir. 2023. Forecast evaluation for data scientists: common pitfalls and best practices. Data Mining and Knowledge Discovery 37, 2 (2023), 788-832.
[33] Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long Short-Term Memory. Neural computation 9, 8 (1997), 1735-1780.
[34] Rob J Hyndman and George Athanasopoulos. 2018. Forecasting: Principles and Practice. OTexts.