Influence-Based Mini-Batching for Graph Neural Networks. - Johannes Gasteiger; Chendi Qian; Stephan Günnemann (LoG, 2022)

Ordered Subgraph Aggregation Networks. - Chendi Qian; Gaurav Rattan; Floris Geerts; Mathias Niepert; Christopher Morris 001 (NeurIPS, 2022)

Advancing Federated Learning in 6G: A Trusted Architecture with Graph-Based Analysis. - Wenxuan Ye; Chendi Qian; Xueli An; Xueqiang Yan; Georg Carle (GLOBECOM, 2023)

Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. - Chendi Qian; Didier Chételat; Christopher Morris 001 (AISTATS, 2024)

Probabilistically Rewired Message-Passing Neural Networks. - Chendi Qian; Andrei Manolache; Kareem Ahmed; Zhe Zeng; Guy Van den Broeck; Mathias Niepert; Christopher Morris 001 (ICLR, 2024)

Probabilistic Graph Rewiring via Virtual Nodes. - Chendi Qian; Andrei Manolache; Christopher Morris 001; Mathias Niepert (NeurIPS, 2024)

Towards graph neural networks for provably solving convex optimization problems. - Chendi Qian; Christopher Morris 001 (CoRR, 2025)

Principled data augmentation for learning to solve quadratic programming problems. - Chendi Qian; Christopher Morris 001 (CoRR, 2025)