5 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Transformers are efficient hierarchical chemical graph learners
Zihan Pengmei, Zimu Li, Chih-chan Tien +2
Transformers, adapted from natural language processing, are emerging as a leading approach for graph representation learning. Contemporary graph transformers often treat nodes or e…
cs.LG2023★ 5 cited
R-Mixup: Riemannian Mixup for Biological Networks
Xuan Kan, Zimu Li, Hejie Cui +6
Biological networks are commonly used in biomedical and healthcare domains to effectively model the structure of complex biological systems with interactions linking biological ent…