Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction

Visualizing data using t-SNE

Van der Maaten, L.; and Hinton, G. 2008 · 2008

Earlier work this paper cites.

Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions

Castro-Neto, M.; Jeong, Y.-S.; Jeong, M.-K.; and Han, L. D. 2009 · 2009

Earlier work this paper cites.

Short-term traffic flow prediction using seasonal ARIMA model with limited input data

Kumar, S. V.; and Vanajakshi, L. 2015 · 2015

Earlier work this paper cites.

Traffic speed prediction and congestion source exploration: A deep learning method

Wang, J.; Gu, Q.; Wu, J.; Liu, G.; and Xiong, Z. 2016 · 2016

Earlier work this paper cites.

Community preserving network embedding

Wang, X.; Cui, P.; Wang, J.; Pei, J.; Zhu, W.; and Yang, S. 2017 · 2017

Earlier work this paper cites.

Deep spatio-temporal residual networks for citywide crowd flows prediction

Zhang, J.; Zheng, Y.; and Qi, D. 2017 · 2017

Earlier work this paper cites.

Spatio-temporal graph convolutional networks: a deep learning framework for traffic forecasting

Yu, B.; Yin, H.; and Zhu, Z. 2018 · 2018

Earlier work this paper cites.

Hetero-ConvLSTM: A deep learning approach to traffic accident prediction on heterogeneous spatio-temporal data

Yuan, Z.; Zhou, X.; and Yang, T. 2018 · 2018

Earlier work this paper cites.

Using self-supervised learning can improve model robustness and uncertainty

Hendrycks, D.; Mazeika, M.; Kadavath, S.; and Song, D. 2019 · 2019

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BERT: Pre-training of deep bidirectional transformers for language understanding

Kenton, J. D. M.-W. C.; and Toutanova, L. K. 2019 · 2019

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Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction

Yao, H.; Tang, X.; Wei, H.; Zheng, G.; and Li, Z. 2019 · 2019

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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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A simple framework for contrastive learning of visual representations

Chen, T.; Kornblith, S.; Norouzi, M.; and Hinton, G. 2020 · 2020

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Interpretable spatiotemporal deep learning model for traffic flow prediction based on potential energy fields

GMAN: A graph multi-attention network for traffic prediction

Zheng, C.; Fan, X.; Wang, C.; and Qi, J. 2020 · 2020

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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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LibCity: An open library for traffic prediction

Wang, J.; Jiang, J.; Jiang, W.; Li, C.; and Zhao, W. X. 2021 · 2021

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Traffic flow forecasting with spatial-temporal graph diffusion network

Zhang, X.; Huang, C.; Xu, Y.; Xia, L.; Dai, P.; Bo, L.; Zhang, J.; and Zheng, Y. 2021 · 2021

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STDEN: Towards physics-guided neural networks for traffic flow prediction

Ji, J.; Wang, J.; Jiang, Z.; Jiang, J.; and Zhang, H. 2022 · 2022

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Traffic Flow Prediction Based on Spatiotemporal Potential Energy Fields

Wang, J.; Ji, J.; Jiang, Z.; and Sun, L. 2022 · 2022