no code implementations • 23 May 2017 • Leye Wang, Xu Geng, Jintao Ke, Chen Peng, Xiaojuan Ma, Daqing Zhang, Qiang Yang
Finally, we use the resulting ensemble of RF and CNN to identify the ridesourcing cars in the candidate pool.
no code implementations • 1 Feb 2018 • Leye Wang, Xu Geng, Xiaojuan Ma, Feng Liu, Qiang Yang
RegionTrans aims to effectively transfer knowledge from a data-rich source city to a data-scarce target city.
3 code implementations • Conference 2019 • Xu Geng, ∗1 Yaguang Li, ∗2 Leye Wang, 1, 3 Lingyu Zhang, 4 Qiang Yang, 1 Jieping Ye, 4 Yan Liu 2, 4
This task is challenging due to the complicated spatiotemporal dependencies among regions.
no code implementations • 27 May 2019 • Xu Geng, Xiyu Wu, Lingyu Zhang, Qiang Yang, Yan Liu, Jieping Ye
To incorporate multiple relationships into spatial feature extraction, we define the problem as a multi-modal machine learning problem on multi-graph convolution networks.
1 code implementation • AAAI 2019 • Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, Yan Liu
This task is challenging due to the complicated spatiotemporal dependencies among regions.
no code implementations • 25 Sep 2019 • Xu Geng, Lingyu Zhang, Shulin Li, Yuanbo Zhang, Lulu Zhang, Leye Wang, Qiang Yang, Hongtu Zhu, Jieping Ye
Deep learning based approaches have been widely used in various urban spatio-temporal forecasting problems, but most of them fail to account for the unsmoothness issue of urban data in their architecture design, which significantly deteriorates their prediction performance.
no code implementations • 30 Jun 2021 • Zhengfei Zheng, Xu Geng, Hai Yang
Therefore, a comprehensive and multifaceted dataset is required to enable more extensive studies in urban computing.