Instance-wise Graph-based Framework for Multivariate Time Series Forecasting

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

Original

Oreshkin, B. N.; Carpov, D.; Chapados, N.; and Bengio, Y. 2019 · 1905

Earlier work this paper cites.

Think globally, act locally: A deep neural network approach to high-dimensional time series forecasting

Original

Sen, R.; Yu, H.-F.; and Dhillon, I. 2019 · 1905

Earlier work this paper cites.

Pytorch: An imperative style, high-performance deep learning library

Original

Paszke, A.; Gross, S.; Massa, F.; Lerer, A.; Bradbury, J.; Chanan, G.; Killeen, T.; Lin, Z.; Gimelshein, N.; Antiga, L.; et al. 2019 · 1912

Earlier work this paper cites.

Gaussian processes for time-series modelling

Roberts, S.; Osborne, M.; Ebden, M.; Reece, S.; Gibson, N.; and Aigrain, S. 2013 · 1984

Earlier work this paper cites.

Long short-term memory

Hochreiter, S.; and Schmidhuber, J. 1997 · 1997

Earlier work this paper cites.

Support vector machine with adaptive parameters in financial time series forecasting

Cao, L.-J.; and Tay, F. E. H. 2003 · 2003

Earlier work this paper cites.

Time series forecasting using a hybrid ARIMA and neural network model

Zhang, G. P. 2003 · 2003

Earlier work this paper cites.

Smoothing, forecasting and prediction of discrete time series

Brown, R. G. 2004 · 2004

Earlier work this paper cites.

Rectifier nonlinearities improve neural network acoustic models

Maas, A. L.; Hannun, A. Y.; and Ng, A. Y. 2013 · 2013

Earlier work this paper cites.

Empirical evaluation of gated recurrent neural networks on sequence modeling

Original

Chung, J.; Gulcehre, C.; Cho, K.; and Bengio, Y. 2014 · 2014

Cited alongside, same era.

Adam: A method for stochastic optimization

Kingma, D. P.; and Ba, J. 2015 · 2015

Cited alongside, same era.

Predicting stock market index using fusion of machine learning techniques

Patel, J.; Shah, S.; Thakkar, P.; and Kotecha, K. 2015 · 2015

Cited alongside, same era.

Recurrent neural network and a hybrid model for prediction of stock returns

Rather, A. M.; Agarwal, A.; and Sastry, V. 2015 · 2015

Cited alongside, same era.

Convolutional LSTM network: A machine learning approach for precipitation nowcasting

Xingjian, S.; Chen, Z.; Wang, H.; Yeung, D.-Y.; Wong, W.-K.; and Woo, W.-c. 2015 · 2015

Cited alongside, same era.

Modeling long-and short-term temporal patterns with deep neural networks

Lai, G.; Chang, W.-C.; Yang, Y.; and Liu, H. 2018 · 2018

Later among the works it cites.

Deeper insights into graph convolutional networks for semi-supervised learning

Li, Q.; Han, Z.; and Wu, X.-M. 2018 · 2018

Later among the works it cites.

Attention based spatial-temporal graph convolutional networks for traffic flow forecasting

Guo, S.; Lin, Y.; Feng, N.; Song, C.; and Wan, H. 2019 · 2019

Later among the works it cites.

Temporal pattern attention for multivariate time series forecasting

Shih, S.-Y.; Sun, F.-K.; and Lee, H.-y. 2019 · 2019

Later among the works it cites.

Towards deeper graph neural networks

Liu, M.; Gao, H.; and Ji, S. 2020 · 2020

Later among the works it cites.

FFORMA: Feature-based forecast model averaging

Montero-Manso, P.; Athanasopoulos, G.; Hyndman, R. J.; and Talagala, T. S. 2020 · 2020