no code implementations • 23 Mar 2021 • Mingming Lu, Ya zhang
Graph Neural Networks (GNNs) have attracted increasing attention due to its successful applications on various graph-structure data.
no code implementations • 17 Sep 2020 • Ya Zhang, Mingming Lu, Haifeng Li
Traffic forecasting is an important prerequisite for the application of intelligent transportation systems in urban traffic networks.
no code implementations • 12 Mar 2019 • Mingming Lu, Kunfang Zhang, Haiying Liu, Naixue Xiong
Most of the existing research methods are to extract spatial structure information on the road network and extract time series information from the historical data.
no code implementations • 9 Mar 2019 • Shangsheng Xie, Mingming Lu
To solve the problem that convolutional neural networks (CNNs) are difficult to process non-grid type relational data like graphs, Kipf et al. proposed a graph convolutional neural network (GCN).
no code implementations • 9 Mar 2019 • Mingming Lu, Dingwu Tan, Naixue Xiong, Zailiang Chen, Haifeng Li
The online programing services, such as Github, TopCoder, and EduCoder, have promoted a lot of social interactions among the service users.
no code implementations • 8 Mar 2019 • Yang Zhang, Mingming Lu
In this paper, the graph neural network matrix filling model (Graph-VAE) based on deep learning can automatically extract features without a large amount of prior knowledge.