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Traffic forecasting is one of the most popular spatio-temporal tasks in the field of machine learning.
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
Wu, Z.; Pan, S.; Long, G.; Jiang, J.; and Zhang, C. 2019 · 1913
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A family of embedded Runge-Kutta formulae
Dormand, J.; and Prince, P. 1980 · 1980
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Freeway performance measurement system: mining loop detector data
Chen, C.; Petty, K.; Skabardonis, A.; Varaiya, P.; and Jia, Z. 2001 · 2001
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Differential equations driven by rough paths
Lyons, T. J.; Caruana, M.; and Lévy, T. 2007 · 2007
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Learning phrase representations using RNN encoder-decoder for statistical machine translation
Cho, K.; van Merrienboer, B.; Gulcehre, C.; Bougares, F.; Schwenk, H.; and Bengio, Y. 2014 · 2014
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Sequence to sequence learning with neural networks
Sutskever, I.; Vinyals, O.; and Le, Q. V. 2014 · 2014
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Forecasting the weather of Nevada: A deep learning approach
Hossain, M.; Rekabdar, B.; Louis, S. J.; and Dascalu, S. 2015 · 2015
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Convolutional LSTM network: A machine learning approach for precipitation nowcasting
Shi, X.; Chen, Z.; Wang, H.; Yeung, D.-Y.; Wong, W.-K.; and Woo, W.-c. 2015 · 2015
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Application of deep convolutional neural networks for detecting extreme weather in climate datasets
Liu, Y.; Racah, E.; Correa, J.; Khosrowshahi, A.; Lavers, D.; Kunkel, K.; Wehner, M.; Collins, W.; et al. 2016 · 2016
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ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events
Racah, E.; Beckham, C.; Maharaj, T.; Kahou, S. E.; Pal, C.; et al. 2016 · 2016
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Sequence to sequence weather forecasting with long short-term memory recurrent neural networks
Zaytar, M. A.; and El Amrani, C. 2016 · 2016
Cited alongside, same era.
Semi-Supervised Classification with Graph Convolutional Networks
Kipf, T. N.; and Welling, M. 2017 · 2017
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Deep learning for precipitation nowcasting: A benchmark and a new model
Shi, X.; Gao, Z.; Lausen, L.; Wang, H.; Yeung, D.-Y.; Wong, W.-k.; and Woo, W.-c. 2017 · 2017
Cited alongside, same era.
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
Bai, S.; Kolter, J. Z.; and Koltun, V. 2018 · 2018
Cited alongside, same era.
Exascale deep learning for climate analytics
Kurth, T.; Treichler, S.; Romero, J.; Mudigonda, M.; Luehr, N.; Phillips, E.; Mahesh, A.; Matheson, M.; Deslippe, J.; Fatica, M.; et al. 2018 · 2018
Cited alongside, same era.
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
Bai, L.; Yao, L.; Li, C.; Wang, X.; and Wang, C. 2020 · 2020
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Time series analysis
Hamilton, J. D. 2020 · 2020
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LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks
Huang, R.; Huang, C.; Liu, Y.; Dai, G.; and Kong, W. 2020 · 2020
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Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting
Song, C.; Lin, Y.; Guo, S.; and Wan, H. 2020 · 2020
Later among the works it cites.
Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
Chen, Y.; Segovia-Dominguez, I.; and Gel, Y. R. 2021 · 2021
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Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting
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Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Li, Y.; Yu, R.; Shahabi, C.; and Liu, Y. 2018 · 2018
Cited alongside, same era.
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
Yu, B.; Yin, H.; and Zhu, Z. 2018 · 2018
Cited alongside, same era.
STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting
Bai, L.; Yao, L.; Kanhere, S. S.; Wang, X.; and Sheng, Q. Z. 2019 · 2019
Cited alongside, same era.
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting
Guo, S.; Lin, Y.; Feng, N.; Song, C.; and Wan, H. 2019 · 2019
Cited alongside, same era.
DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting
Huang, S.; Wang, D.; Wu, X.; and Tang, A. 2019 · 2019
Cited alongside, same era.
Ensemble recurrent neural network based probabilistic wind speed forecasting approach
Cheng, L.; Zang, H.; Ding, T.; Sun, R.; Wang, M.; Wei, Z.; and Sun, G. 2018a
Cited in the paper.
A neural attention model for urban air quality inference: Learning the weights of monitoring stations
Cheng, W.; Shen, Y.; Zhu, Y.; and Huang, L. 2018b
Cited in the paper.
Fang, Z.; Long, Q.; Song, G.; and Xie, K. 2021 · 2021
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Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting
Li, M.; and Zhu, Z. 2021 · 2021
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Deep Learning-Based Weather Prediction: A Survey
Ren, X.; Li, X.; Ren, K.; Song, J.; Xu, Z.; Deng, K.; and Wang, X. 2021 · 2021
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Spatio-temporal Weather Forecasting and Attention Mechanism on Convolutional LSTMs
Tekin, S. F.; Karaahmetoglu, O.; Ilhan, F.; Balaban, I.; and Kozat, S. S. 2021 · 2021
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