6 citations · 6 across the 4 of their papers we have counts for
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cs.LG2023
Supercharging Graph Transformers with Advective Diffusion
Qitian Wu, Chenxiao Yang, Kaipeng Zeng +1
The capability of generalization is a cornerstone for the success of modern learning systems. For non-Euclidean data, e.g., graphs, that particularly involves topological structure…
cs.LG2022★ 6 cited
Molecule Generation for Drug Design: a Graph Learning Perspective
Nianzu Yang, Huaijin Wu, Kaipeng Zeng +2
Machine learning, particularly graph learning, is gaining increasing recognition for its transformative impact across various fields. One such promising application is in the realm…