57 citations · 74 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks
Haoran Liu, Bokun Wang, Jianling Wang +3
As powerful tools for representation learning on graphs, graph neural networks (GNNs) have played an important role in applications including social networks, recommendation system…
cs.LG2022★ 17 cited
Learning Hierarchical Protein Representations via Complete 3D Graph Networks
Limei Wang, Haoran Liu, Yi Liu +2
We consider representation learning for proteins with 3D structures. We build 3D graphs based on protein structures and develop graph networks to learn their representations. Depen…
cs.LG2021★ 57 cited
DIG: A Turnkey Library for Diving into Graph Deep Learning Research
Meng Liu, Youzhi Luo, Limei Wang +13
Although there exist several libraries for deep learning on graphs, they are aiming at implementing basic operations for graph deep learning. In the research community, implementin…