% Key papers for Neural and local graph clustering (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2019_linkage_14470,
  title = {{Linkage Based Face Clustering via Graph Convolution Network}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_learning_14435,
  title = {{Learning to Cluster Faces on an Affinity Graph}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{aaai2023_hard_3819,
  title = {{Hard Sample Aware Network for Contrastive Deep Graph Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26071},
}

@inproceedings{cvpr2020_adaptive_15120,
  title = {{Adaptive Graph Convolutional Network With Attention Graph Clustering for Co-Saliency Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_learning_15807,
  title = {{Learning to Cluster Faces via Confidence and Connectivity Estimation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2017_learning_56411,
  title = {{Learning A Structured Optimal Bipartite Graph for Co-Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9193},
}

@inproceedings{aaai2021_multiple_1039,
  title = {{Multiple Kernel Clustering with Kernel k-Means Coupled Graph Tensor Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09411-multiple-kernel-clustering-with-kernel-k-means-coupled-graph-tensor-learning/},
}

@inproceedings{aaai2018_bayesian_102375,
  title = {{Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11642},
}

@inproceedings{aaai2021_graph_682,
  title = {{Graph Neural Network to Dilute Outliers for Refactoring Monolith Application}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/00072-graph-neural-network-to-dilute-outliers-for-refactoring-monolith-application/},
}

@inproceedings{aaai2024_attribute_5222,
  title = {{Attribute-Missing Graph Clustering Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29464},
}

@inproceedings{aaai2019_incorporating_99688,
  title = {{Incorporating Network Embedding into Markov Random Field for Better Community Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3781},
}

@inproceedings{aaai2017_simultaneous_105678,
  title = {{Simultaneous Clustering and Ensemble}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10720},
}

@inproceedings{aaai2020_gromov_102258,
  title = {{Gromov-Wasserstein Factorization Models for Graph Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6120},
}

@inproceedings{aaai2021_interpretable_796,
  title = {{Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04608-interpretable-clustering-on-dynamic-graphs-with-recurrent-graph-neural-networks/},
}

@inproceedings{aaai2024_dgcluster_5558,
  title = {{DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28983},
}

@inproceedings{icml2017_capacity_36090,
  title = {{Capacity Releasing Diffusion for Speed and Locality}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/827},
}

@inproceedings{neurips2019_variance_59175,
  title = {{Variance Reduction in Bipartite Experiments through Correlation Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14269},
}

@inproceedings{aaai2023_scalable_4608,
  title = {{Scalable Attributed-Graph Subspace Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25918},
}

@inproceedings{aaai2024_tensorized_7520,
  title = {{Tensorized Label Learning on Anchor Graph}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29257},
}

@inproceedings{neurips2016_community_55634,
  title = {{Community Detection on Evolving Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6956},
}

@inproceedings{aaai2024_upper_7729,
  title = {{Upper Bounding Barlow Twins: A Novel Filter for Multi-Relational Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29383},
}

@inproceedings{aaai2024_learning_6474,
  title = {{Learning Persistent Community Structures in Dynamic Networks via Topological Data Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28706},
}

@inproceedings{aaai2025_one_10188,
  title = {{One Node One Model: Featuring the Missing-Half for Graph Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35473},
}

@inproceedings{cvpr2024_fine_23471,
  title = {{Fine-Grained Bipartite Concept Factorization for Clustering}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29518},
}

@inproceedings{neurips2024_the_72829,
  title = {{The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94570},
}

@inproceedings{neurips2024_community_73039,
  title = {{Community Detection Guarantees using Embeddings Learned by Node2Vec}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94384},
}

@inproceedings{icml2024_lsenet_44139,
  title = {{LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34313},
}

@inproceedings{neurips2025_adjusted_75778,
  title = {{Adjusted Count Quantification Learning on Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=BumyAsRGGm},
}

@inproceedings{aaai2025_sccs_10595,
  title = {{SCCS: Deep Neural Spectral Clustering for Self-Supervised Subcellular Structure Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32419},
}

@inproceedings{iclr2024_local_33738,
  title = {{Local Graph Clustering with Noisy Labels}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19337},
}

@inproceedings{icml2024_cluster_45457,
  title = {{Cluster-Aware Similarity Diffusion for Instance Retrieval}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32994},
}

@inproceedings{icml2024_pruned_45547,
  title = {{Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32905},
}

@inproceedings{icml2025_tango_49118,
  title = {{TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43507},
}

@inproceedings{icml2026_bipartite_50655,
  title = {{Bipartite Graph Attention-based Clustering for Large-scale scRNA-seq Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=EVnMERXEvC},
}

@inproceedings{icml2026_estimating_51401,
  title = {{Estimating Correlation Clustering Cost in Node-Arrival Stream}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=LplfRFhduF},
}

@inproceedings{neurips2025_optimal_77662,
  title = {{Optimal Graph Clustering without Edge Density Signals}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=WCPAHpVAUp},
}

@inproceedings{neurips2025_dgcbench_78321,
  title = {{DGCBench: A Deep Graph Clustering Benchmark}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=dKVUUZfcW9},
}