67 citations · 164 across the 12 of their papers we have counts for
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cs.LG2020★ 3 cited
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks
Hao Tang, Zhiao Huang, Jiayuan Gu +2
Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems. Tak…
cs.LG2018★ 29 cited
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation
Liwei Wang, Lunjia Hu, Jiayuan Gu +4
It is widely believed that learning good representations is one of the main reasons for the success of deep neural networks. Although highly intuitive, there is a lack of theory an…