623 citations · 961 across the 7 of their papers we have counts for
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cs.LG2021★ 623 cited
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting
Zheng Fang, Qingqing Long, Guojie Song +1
Spatial-temporal forecasting has attracted tremendous attention in a wide range of applications, and traffic flow prediction is a canonical and typical example. The complex and lon…
cs.AI2021
Explicit Semantic Cross Feature Learning via Pre-trained Graph Neural Networks for CTR Prediction
Feng Li, Bencheng Yan, Qingqing Long +4
Cross features play an important role in click-through rate (CTR) prediction. Most of the existing methods adopt a DNN-based model to capture the cross features in an implicit mann…
cs.LG2021★ 1 cited
Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels
Qingqing Long, Yilun Jin, Yi Wu +1
Graph neural networks (GNNs) have achieved tremendous success in graph mining. However, the inability of GNNs to model substructures in graphs remains a significant drawback. Speci…