Multivariate Time Series Forecasting: A Review

Author:

Mendis Kasun1ORCID,Wickramasinghe Manjusri1ORCID,Marasinghe Pasindu1ORCID

Affiliation:

1. University of Colombo School of Computing, Sri Lanka

Publisher

ACM

Reference33 articles.

1. Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural Machine Translation by Jointly Learning to Align and Translate. CoRR abs/1409.0473 (2014).

2. Shaojie Bai, J. Zico Kolter, and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. ArXiv abs/1803.01271 (2018).

3. Anastasia Borovykh, Sander M. Bohté, and Cornelis W. Oosterlee. 2017. Conditional Time Series Forecasting with Convolutional Neural Networks. arXiv: Machine Learning (2017).

4. Diogo Vieira Carvalho, Eduardo Marques Pereira, and Jaime S. Cardoso. 2019. Machine Learning Interpretability: A Survey on Methods and Metrics. Electronics (2019).

5. Yen-Yu Chang, Fan-Yun Sun, Yueh-Hua Wu, and Shou-De Lin. 2018. A Memory-Network Based Solution for Multivariate Time-Series Forecasting. ArXiv abs/1809.02105 (2018).

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