A Game-Theoretic Approach for Improving Generalization Ability of TSP Solvers. - Chenguang Wang 011; Yaodong Yang 001; Oliver Slumbers; Congying Han; Tiande Guo; Haifeng Zhang 002; Jun Wang 012 (CoRR, 2021)

Analysis of Graph Neural Networks with Theory of Markov Chains. - Weichen Zhao; Chenguang Wang 011; Congying Han; Tiande Guo (CoRR, 2022)

Exploring Over-smoothing in Graph Attention Networks from the Markov Chain Perspective. - Weichen Zhao; Chenguang Wang 011; Congying Han; Tiande Guo (FAIML, 2023)

Solving uncapacitated P-Median problem with reinforcement learning assisted by graph attention networks. - Chenguang Wang 011; Congying Han; Tiande Guo; Man Ding (Appl. Intell., 2023)

Efficient Training of Multi-task Neural Solver with Multi-armed Bandits. - Chenguang Wang 011; Tianshu Yu 001 (CoRR, 2023)

Learning graph representation by aggregating subgraphs via mutual information maximization. - Ziwen Liu; Chenguang Wang 011; Congying Han; Tiande Guo (Neurocomputing, 2023)

Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory. - Weichen Zhao; Chenguang Wang 011; Xinyan Wang 004; Congying Han; Tiande Guo; Tianshu Yu 001 (CoRR, 2024)

Towards Principled Task Grouping for Multi-Task Learning. - Chenguang Wang 011; Xuanhao Pan; Tianshu Yu 001 (CoRR, 2024)

Rethinking the "Heatmap + Monte Carlo Tree Search" Paradigm for Solving Large Scale TSP. - Xuanhao Pan; Chenguang Wang 011; Chaolong Ying; Ye Xue; Tianshu Yu 001 (CoRR, 2024)

ASP: Learn a Universal Neural Solver! - Chenguang Wang 011; Zhouliang Yu; Stephen McAleer; Tianshu Yu 001; Yaodong Yang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Efficient Training of Multi-task Neural Solver for Combinatorial Optimization. - Chenguang Wang 011; Zhang-Hua Fu; Pinyan Lu; Tianshu Yu 001 (Trans. Mach. Learn. Res., 2025)