3 papers
cs.LG2026
Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection
Xudong Wang, Ziheng Sun, Chris Ding +1
This work proposes a framework LGKDE that learns kernel density estimation for graphs. The key challenge in graph density estimation lies in effectively capturing both structural p…
cs.LG2026
Adaptive Riemannian Graph Neural Networks
Xudong Wang, Chris Ding, Tongxin Li +1
Graph data often exhibits complex geometric heterogeneity, where structures with varying local curvature, such as tree-like hierarchies and dense communities, coexist within a sing…
cs.LG2025
Explainable Graph Representation Learning via Graph Pattern Analysis
Xudong Wang, Ziheng Sun, Chris Ding +1
Explainable artificial intelligence (XAI) is an important area in the AI community, and interpretability is crucial for building robust and trustworthy AI models. While previous wo…