2 citations · 4 across the 3 of their papers we have counts for
3 papers
q-bio.GN2025★ 1 cited
Deep Learning and Explainable AI: New Pathways to Genetic Insights
Chenyu Wang, Chaoying Zuo, Zihan Su +4
Deep learning-based AI models have been extensively applied in genomics, achieving remarkable success across diverse applications. As these models gain prominence, there exists an…
cs.LG2024★ 1 cited
Verbalized Graph Representation Learning: A Fully Interpretable Graph Model Based on Large Language Models Throughout the Entire Process
Xingyu Ji, Jiale Liu, Lu Li +2
Representation learning on text-attributed graphs (TAGs) has attracted significant interest due to its wide-ranging real-world applications, particularly through Graph Neural Netwo…
cs.LG2024★ 2 cited
DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks
Zeyu Zhang, Lu Li, Shuyan Wan +5
The paper discusses signed graphs, which model friendly or antagonistic relationships using edges marked with positive or negative signs, focusing on the task of link sign predicti…