no code implementations • 6 Apr 2022 • Peng Xie, Minbo Ma, Tianrui Li, Shenggong Ji, Shengdong Du, Zeng Yu, Junbo Zhang
Second, we employ a dynamic graph relationship learning module to learn dynamic spatial relationships between metro stations without a predefined graph adjacency matrix.
no code implementations • 22 Jan 2022 • Minbo Ma, Peng Xie, Fei Teng, Tianrui Li, Bin Wang, Shenggong Ji, Junbo Zhang
In this paper, we propose a novel Hierarchical Spatio-Temporal Graph Neural Network (HiSTGNN) to model cross-regional spatio-temporal correlations among meteorological variables in multiple stations.
no code implementations • 24 Apr 2021 • Peng Xie, Wenyuan Tao, Jie Li, Wentao Huang, Siming Chen
The core of the approach is a subset embedding network (SEN) that represents a group of subsets as uniformly-formatted embeddings.
no code implementations • 19 Mar 2020 • Donghuan Lu, Sujun Zhao, Peng Xie, Kai Ma, Li-Juan Liu, Yefeng Zheng
To ensure the quality of reconstructed neurons and provide guidance for annotators to improve their efficiency, we propose a deep learning based quality control method for neuron reconstruction in this paper.
no code implementations • 26 Aug 2019 • Peng Xie, Tianrui Li, Jia Liu, Shengdong Du, Xin Yang, Junbo Zhang
Urban spatial-temporal flows prediction is of great importance to traffic management, land use, public safety, etc.