publications

2024

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    Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems
    Chendi Qian, Didier Chételat, and Christopher Morris
    In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, 2024
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    Probabilistic Graph Rewiring via Virtual Nodes
    Chendi Qian, Andrei Manolache, Christopher Morris, and Mathias Niepert
    2024

2023

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    Probabilistically Rewired Message-Passing Neural Networks
    Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Broeck, Mathias Niepert, and Christopher Morris
    2023
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    Probabilistic Task-Adaptive Graph Rewiring
    Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Broeck, Mathias Niepert, and Christopher Morris
    In ICML 2023 Workshop on Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators, 2023
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    Advancing Federated Learning in 6G: A Trusted Architecture with Graph-based Analysis
    Wenxuan Ye, Chendi Qian, Xueli An, Xueqiang Yan, and Georg Carle
    In GLOBECOM 2023-2023 IEEE Global Communications Conference, 2023

2022

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    Ordered subgraph aggregation networks
    Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, and Christopher Morris
    Advances in Neural Information Processing Systems, 2022
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    Influence-based mini-batching for graph neural networks
    Johannes Gasteiger, Chendi Qian, and Stephan Günnemann
    In Learning on Graphs Conference, 2022