364 citations · 460 across the 28 of their papers we have counts for
5 papers · 1 filter
Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce
Borui Ye, Shuo Yang, Binbin Hu +5
E-commerce has gone a long way in empowering merchants through the internet. In order to store the goods efficiently and arrange the marketing resource properly, it is important fo…
KGNN: Distributed Framework for Graph Neural Knowledge Representation
Binbin Hu, Zhiyang Hu, Zhiqiang Zhang +2
Knowledge representation learning has been commonly adopted to incorporate knowledge graph (KG) into various online services. Although existing knowledge representation learning me…
Neural Graph Matching for Pre-training Graph Neural Networks
Yupeng Hou, Binbin Hu, Wayne Xin Zhao +3
Recently, graph neural networks (GNNs) have been shown powerful capacity at modeling structural data. However, when adapted to downstream tasks, it usually requires abundant task-s…
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022
Qian Zhao, Shuo Yang, Binbin Hu +5
Temporal link prediction, as one of the most crucial work in temporal graphs, has attracted lots of attention from the research area. The WSDM Cup 2022 seeks for solutions that pre…
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift
Hongrui Liu, Binbin Hu, Xiao Wang +3
Graph Convolutional Networks (GCNs) have recently attracted vast interest and achieved state-of-the-art performance on graphs, but its success could typically hinge on careful trai…