42 citations · 72 across the 4 of their papers we have counts for
4 papers
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching
Fang Wu, Siyuan Li, Xurui Jin +4
The success of graph neural networks (GNNs) provokes the question about explainability: ``Which fraction of the input graph is the most determinant of the prediction?'' Particularl…
Pre-training of Equivariant Graph Matching Networks with Conformation Flexibility for Drug Binding
Fang Wu, Shuting Jin, Yinghui Jiang +7
The latest biological findings observe that the traditional motionless 'lock-and-key' theory is not generally applicable because the receptor and ligand are constantly moving. None…
Robust Weakly Supervised Learning for COVID-19 Recognition Using Multi-Center CT Images
Qinghao Ye, Yuan Gao, Weiping Ding +8
The world is currently experiencing an ongoing pandemic of an infectious disease named coronavirus disease 2019 (i.e., COVID-19), which is caused by the severe acute respiratory sy…
Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification from CT Images
Shaoping Hu, Yuan Gao, Zhangming Niu +9
An outbreak of a novel coronavirus disease (i.e., COVID-19) has been recorded in Wuhan, China since late December 2019, which subsequently became pandemic around the world. Althoug…