% Key papers for Diffusion-based graph generation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2018_graphgan_105763,
  title = {{GraphGAN: Graph Representation Learning With Generative Adversarial Nets}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11872},
}

@inproceedings{icml2018_graphrnn_36728,
  title = {{GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2373},
}

@inproceedings{icml2018_netgan_36864,
  title = {{NetGAN: Generating Graphs via Random Walks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2193},
}

@inproceedings{neurips2019_efficient_58189,
  title = {{Efficient Graph Generation with Graph Recurrent Attention Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13582},
}

@inproceedings{iclr2020_reinforcement_29553,
  title = {{Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HygnDhEtvr},
}

@inproceedings{iclr2023_digress_32670,
  title = {{DiGress: Discrete Denoising diffusion for graph generation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11556},
}

@inproceedings{iclr2019_generative_28792,
  title = {{Generative Code Modeling with Graphs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/1000},
}

@inproceedings{neurips2019_graph_58351,
  title = {{Graph Normalizing Flows}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14292},
}

@inproceedings{aaai2017_regularized_103937,
  title = {{Regularized Diffusion Process for Visual Retrieval}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11216},
}

@inproceedings{neurips2019_conditional_58027,
  title = {{Conditional Structure Generation through Graph Variational Generative Adversarial Nets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13353},
}

@inproceedings{cvpr2021_hdmapgen_17100,
  title = {{HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{icml2018_contextual_36595,
  title = {{Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2084},
}

@inproceedings{icml2019_graphite_37411,
  title = {{Graphite: Iterative Generative Modeling of Graphs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4008},
}

@inproceedings{icml2022_score_41153,
  title = {{Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/18139},
}

@inproceedings{aaai2023_boundary_3198,
  title = {{Boundary Graph Neural Networks for 3D Simulations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26092},
}

@inproceedings{aaai2020_convergence_102700,
  title = {{Convergence of Opinion Diffusion is PSPACE-Complete}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6197},
}

@inproceedings{aaai2019_learning_99947,
  title = {{Learning Diffusions without Timestamps}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3833},
}

@inproceedings{neurips2022_deep_65868,
  title = {{Deep Generative Model for Periodic Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54872},
}

@inproceedings{aaai2020_graph_100273,
  title = {{Graph-Driven Generative Models for Heterogeneous Multi-Task Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5446},
}

@inproceedings{aaai2021_content_303,
  title = {{Content Learning with Structure-Aware Writing: A Graph-Infused Dual Conditional Variational Autoencoder for Automatic Storytelling}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/06021-content-learning-with-structure-aware-writing-a-graph-infused-dual-conditional-variational-autoencoder-for-automatic-storytelling/},
}

@inproceedings{aaai2024_hyperbolic_6237,
  title = {{Hyperbolic Graph Diffusion Model}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29512},
}

@inproceedings{aaai2025_gsdiff_9293,
  title = {{GSDiff: Synthesizing Vector Floorplans via Geometry-enhanced Structural Graph Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33904},
}

@inproceedings{aaai2024_dag_5548,
  title = {{DAG-Aware Variational Autoencoder for Social Propagation Graph Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28694},
}

@inproceedings{cvpr2025_brepgiff_25616,
  title = {{BrepGiff: Lightweight Generation of Complex B-rep with 3D GAT Diffusion}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35112},
}

@inproceedings{neurips2024_fairwire_72425,
  title = {{FairWire: Fair Graph Generation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94931},
}

@inproceedings{aaai2025_glad_9278,
  title = {{GLAD: Improving Latent Graph Generative Modeling with Simple Quantization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34169},
}

@inproceedings{neurips2024_pard_74470,
  title = {{Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93104},
}

@inproceedings{icml2024_hyperbolic_43528,
  title = {{Hyperbolic Geometric Latent Diffusion Model for Graph Generation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34924},
}

@inproceedings{neurips2024_discrete_72713,
  title = {{Discrete-state Continuous-time Diffusion for Graph Generation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94674},
}

@inproceedings{aaai2025_fap_9100,
  title = {{FAP-CD: Fairness-Driven Age-Friendly Community Planning via Conditional Diffusion Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35036},
}

@inproceedings{iclr2024_higen_34166,
  title = {{HiGen: Hierarchical Graph Generative Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18909},
}

@inproceedings{icml2024_a_45841,
  title = {{A Graph is Worth \$K\$ Words: Euclideanizing Graph using Pure Transformer}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32612},
}

@inproceedings{icml2025_graphgpt_46075,
  title = {{GraphGPT: Generative Pre-trained Graph Eulerian Transformer}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46483},
}

@inproceedings{icml2025_graph_46702,
  title = {{Graph Generative Pre-trained Transformer}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45870},
}

@inproceedings{icml2025_defog_46936,
  title = {{DeFoG: Discrete Flow Matching for Graph Generation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45644},
}

@inproceedings{icml2026_flag_55393,
  title = {{FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=yY7rywRtlI},
}

@inproceedings{neurips2024_graph_70780,
  title = {{Graph Diffusion Policy Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96349},
}

@inproceedings{neurips2024_unifying_73706,
  title = {{Unifying Generation and Prediction on Graphs with Latent Graph Diffusion}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93791},
}

@inproceedings{aaai2026_ngtm_107812,
  title = {{NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40164},
}

@inproceedings{iclr2024_efficient_33530,
  title = {{Efficient and Scalable Graph Generation through Iterative Local Expansion}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19545},
}