3 papers
cs.AI2026
Towards Faithful Graph Explanations with Synergistic Edge Effects via Granular Balls
Jiancu Chen, Shuyin Xia, Guan Wang +2
Instance-level explanations aim to reveal the rationale behind a model's decisions for a specific graph. Previous methods explain graph neural networks (GNNs) by selecting importan…
cs.AI2025
GBGC: Efficient and Adaptive Graph Coarsening via Granular-ball Computing
Shuyin Xia, Guan Wang, Gaojie Xu +2
The objective of graph coarsening is to generate smaller, more manageable graphs while preserving key information of the original graph. Previous work were mainly based on the pers…
cs.LG2025
GBO:AMulti-Granularity Optimization Algorithm via Granular-ball for Continuous Problems
Shuyin Xia, Xinyu Lin, Guan Wang +4
Optimization problems aim to find the optimal solution, which is becoming increasingly complex and difficult to solve. Traditional evolutionary optimization methods always overlook…