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Road traffic forecasting plays a critical role in smart city initiatives and has experienced significant advancements thanks to the power of deep learning in capturing non-linear patterns of traffic data.
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Jake Kononov, Barbara Bailey, and Bryan K Allery · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Dennis Luxen and Christian Vetter · 2011
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Jake Kononov, David Reeves, Catherine Durso, and Bryan K Allery · 2012
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The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
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Convolutional neural networks on graphs with fast localized spectral filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2017
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Diffusion convolutional recurrent neural network: Data-driven traffic forecasting
Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu · 2018
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Geoman: Multi-level attention networks for geo-sensory time series prediction
Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, and Yu Zheng · 2018
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Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting
Bing Yu, Haoteng Yin, and Zhanxing Zhu · 2018
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Attention based spatial-temporal graph convolutional networks for traffic flow forecasting
Shengnan Guo, Youfang Lin, Ning Feng, Chao Song, and Huaiyu Wan · 2019
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Urban traffic prediction from spatio-temporal data using deep meta learning
Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, and Junbo Zhang · 2019
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Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman · 2019
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Graph wavenet for deep spatial-temporal graph modeling
Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, and Chengqi Zhang · 2019
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Datasheets for datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé Iii, and Kate Crawford · 2021
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Dynamic and multi-faceted spatio-temporal deep learning for traffic speed forecasting
Liangzhe Han, Bowen Du, Leilei Sun, Yanjie Fu, Yisheng Lv, and Hui Xiong · 2021
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Dynamic graph convolutional recurrent network for traffic prediction: Benchmark and solution
Fuxian Li, Jie Feng, Huan Yan, Guangyin Jin, Fan Yang, Funing Sun, Depeng Jin, and Yong Li · 2021
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Revisiting convolutional neural networks for citywide crowd flow analytics
Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, and David S Rosenblum · 2021
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Deep learning for road traffic forecasting: Does it make a difference?
Eric L Manibardo, Ibai Laña, and Javier Del Ser · 2021
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Lei Bai, Lina Yao, Can Li, Xianzhi Wang, and Can Wang · 2020
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Spectral temporal graph neural network for multivariate time-series forecasting
Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, et al · 2020
Cited alongside, same era.
Open graph benchmark: Datasets for machine learning on graphs
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec · 2020
Cited alongside, same era.
Graph-partitioning-based diffusion convolutional recurrent neural network for large-scale traffic forecasting
Tanwi Mallick, Prasanna Balaprakash, Eric Rask, and Jane Macfarlane · 2020
Cited alongside, same era.
Spatial-temporal synchronous graph convolutional networks: A new framework for spatial-temporal network data forecasting
Chao Song, Youfang Lin, Shengnan Guo, and Huaiyu Wan · 2020
Cited alongside, same era.
Spatial-temporal transformer networks for traffic flow forecasting
Mingxing Xu, Wenrui Dai, Chunmiao Liu, Xing Gao, Weiyao Lin, Guo-Jun Qi, and Hongkai Xiong · 2020
Cited alongside, same era.
Spatial-temporal graph ode networks for traffic flow forecasting
Zheng Fang, Qingqing Long, Guojie Song, and Kunqing Xie · 2021
Cited alongside, same era.
Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, and Noseong Park · 2022
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Dstagnn: Dynamic spatial-temporal aware graph neural network for traffic flow forecasting
Shiyong Lan, Yitong Ma, Weikang Huang, Wenwu Wang, Hongyu Yang, and Pyang Li · 2022
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When do contrastive learning signals help spatio-temporal graph forecasting?
Xu Liu, Yuxuan Liang, Chao Huang, Yu Zheng, Bryan Hooi, and Roger Zimmermann · 2022
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Decoupled dynamic spatial-temporal graph neural network for traffic forecasting
Zezhi Shao, Zhao Zhang, Wei Wei, Fei Wang, Yongjun Xu, Xin Cao, and Christian S Jensen · 2022
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When spatio-temporal meet wavelets: Disentangled traffic forecasting via efficient spectral graph attention networks
Yuchen Fang, Yanjun Qin, Haiyong Luo, Fang Zhao, Bingbing Xu, Liang Zeng, and Chenxing Wang · 2023
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Do we really need graph neural networks for traffic forecasting?
Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, and Roger Zimmermann · 2023
Closest in time.