Dong Wen — accepted AI-conference papers

2026

Towards Generative Graph Matching for Graph Edit Distance Computation

Wei Huang, Hanchen Wang, Dong Wen, Wenjie Zhang, Ying Zhang, Xuemin Lin

ICML 2026poster

Graph Edit Distance (GED), which aims to find an edit path with minimum number of edit operations to transform one graph into another, is a fundamental NP-hard problem and a widely used graph similarity measure. Recent matching-based hybrid approaches have demonstrated better scalability than A* sea…

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2025

Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN

Wei Huang, Hanchen Wang, Dong Wen, Shaozhen Ma, Wenjie Zhang, Xuemin Lin

NeurIPS 2025poster

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 GED solver has shown promising performance by formulating GED as a bipartite graph matching problem, then leveraging a…

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