% Key papers for Deep learning for graph matching (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2019_graph_37406,
  title = {{Graph Matching Networks for Learning the Similarity of Graph Structured Objects}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4018},
}

@inproceedings{cvpr2018_deep_12971,
  title = {{Deep Learning of Graph Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Zanfir_Deep_Learning_of_CVPR_2018_paper.html},
}

@inproceedings{cvpr2021_learnable_17253,
  title = {{Learnable Graph Matching: Incorporating Graph Partitioning With Deep Feature Learning for Multiple Object Tracking}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{icml2019_gromov_37415,
  title = {{Gromov-Wasserstein Learning for Graph Matching and Node Embedding}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3845},
}

@inproceedings{cvpr2022_clustergnn_18469,
  title = {{ClusterGNN: Cluster-Based Coarse-To-Fine Graph Neural Network for Efficient Feature Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2020_learning_15746,
  title = {{Learning Combinatorial Solver for Graph Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2020_deep_29539,
  title = {{Deep Graph Matching Consensus}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HyeJf1HKvS},
}

@inproceedings{iclr2020_learning_29786,
  title = {{Learning deep graph matching with channel-independent embedding and Hungarian attention}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rJgBd2NYPH},
}

@inproceedings{cvpr2021_deep_16819,
  title = {{Deep Graph Matching Under Quadratic Constraint}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{neurips2019_scalable_58950,
  title = {{Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13486},
}

@inproceedings{aaai2022_interpretable_2261,
  title = {{Interpretable Neural Subgraph Matching for Graph Retrieval}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08115-interpretable-neural-subgraph-matching-for-graph-retrieval/},
}

@inproceedings{cvpr2021_layoutgmn_17250,
  title = {{LayoutGMN: Neural Graph Matching for Structural Layout Similarity}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2022_multi_19391,
  title = {{Multi-Robot Active Mapping via Neural Bipartite Graph Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{neurips2020_graduated_59961,
  title = {{Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17061},
}

@inproceedings{cvpr2022_graph_18957,
  title = {{Graph-Context Attention Networks for Size-Varied Deep Graph Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2021_ia_740,
  title = {{IA-GM: A Deep Bidirectional Learning Method for Graph Matching}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/03474-ia-gm-a-deep-bidirectional-learning-method-for-graph-matching/},
}

@inproceedings{cvpr2023_deep_20746,
  title = {{Deep Learning of Partial Graph Matching via Differentiable Top-K}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22445},
}

@inproceedings{cvpr2020_determinant_15406,
  title = {{Determinant Regularization for Gradient-Efficient Graph Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2023_g_21033,
  title = {{G-MSM: Unsupervised Multi-Shape Matching With Graph-Based Affinity Priors}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22834},
}

@inproceedings{aaai2021_proxy_1211,
  title = {{Proxy Graph Matching with Proximal Matching Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09808-proxy-graph-matching-with-proximal-matching-networks/},
}

@inproceedings{aaai2024_discrete_5707,
  title = {{Discrete Cycle-Consistency Based Unsupervised Deep Graph Matching}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28332},
}

@inproceedings{cvpr2024_adaptive_22730,
  title = {{Adaptive Softassign via Hadamard-Equipped Sinkhorn}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31238},
}

@inproceedings{cvpr2024_fc_23427,
  title = {{FC-GNN: Recovering Reliable and Accurate Correspondences from Interferences}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29645},
}

@inproceedings{icml2024_navigating_45017,
  title = {{Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33435},
}

@inproceedings{neurips2024_iteratively_74297,
  title = {{Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93261},
}

@inproceedings{iclr2024_m3c_33816,
  title = {{M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19259},
}

@inproceedings{icml2024_magnolia_44645,
  title = {{MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33807},
}

@inproceedings{neurips2025_towards_75178,
  title = {{Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=59HMRbpQ25},
}

@inproceedings{iclr2025_learning_83829,
  title = {{Learning Partial Graph Matching via Optimal Partial Transport}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27991},
}

@inproceedings{neurips2026_chaining_91921,
  title = {{Chaining 2-FWL GNNs for Combinatorial Graph Alignment}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151502},
}

@inproceedings{icml2025_position_46747,
  title = {{Position: Graph Matching Systems Deserve Better Benchmarks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/40161},
}

@inproceedings{icml2026_towards_54898,
  title = {{Towards Generative Graph Matching for Graph Edit Distance Computation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=thuyfHsRIu},
}