3 citations · 3 across the 11 of their papers we have counts for
4 papers · 1 filter
Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN
Wei Huang, Hanchen Wang, Dong Wen +3
Graph Edit Distance (GED) is a fundamental graph similarity metric widely used in various applications. However, computing GED is an NP-hard problem. Recent state-of-the-art hybrid…
DiffGED: Computing Graph Edit Distance via Diffusion-based Graph Matching
Wei Huang, Hanchen Wang, Dong Wen +3
The Graph Edit Distance (GED) problem, which aims to compute the minimum number of edit operations required to transform one graph into another, is a fundamental challenge in graph…
Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning
Guangxin Su, Yifan Zhu, Wenjie Zhang +2
Graph representation learning, involving both node features and graph structures, is crucial for real-world applications but often encounters pervasive noise. State-of-the-art meth…
GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions
Hanchen Wang, Defu Lian, Ying Zhang +2
Entity interaction prediction is essential in many important applications such as chemistry, biology, material science, and medical science. The problem becomes quite challenging w…