publications

2026

  1. ufl.png
    Learning to Approximate Uniform Facility Location via Graph Neural Networks
    Chendi Qian, Christopher Morris, Stefanie Jegelka, and Christian Sohler
    Forty-Third International Conference on Machine Learning, 2026
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    On the Expressive Power of GNNs to Solve Linear SDPs
    Chendi Qian, and Christopher Morris
    Forty-Third International Conference on Machine Learning, 2026
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    GraIP: A Benchmarking Framework For Neural Graph Inverse Problems
    Semih Cantürk, Andrei Manolache, Arman Mielke, Chendi Qian, Antoine Siraudin, Christopher Morris, Mathias Niepert, and Guy Wolf
    arXiv preprint arXiv:2601.18917, 2026

2025

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    GraphBench: Next-generation graph learning benchmarking
    Timo Stoll, Chendi Qian, Ben Finkelshtein, Ali Parviz, Darius Weber, Fabrizio Frasca, Hadar Shavit, Antoine Siraudin, Arman Mielke, Marie Anastacio, and  others
    arXiv preprint arXiv:2512.04475, 2025
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    Principled data augmentation for learning to solve quadratic programming problems
    Chendi Qian, and Christopher Morris
    Advances in Neural Information Processing Systems, 2025
    Spotlight

2024

  1. ipr_rewire.png
    Probabilistic Graph Rewiring via Virtual Nodes
    Chendi Qian, Andrei Manolache, Christopher Morris, and Mathias Niepert
    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

2023

  1. pr_mpnn.png
    Probabilistically Rewired Message-Passing Neural Networks
    Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Broeck, Mathias Niepert, and Christopher Morris
    2023
  2. pr_workshop.jpg
    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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    Influence-based mini-batching for graph neural networks
    Johannes Gasteiger, Chendi Qian, and Stephan Günnemann
    In Learning on Graphs Conference, 2022
    Oral presentation
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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