% Key papers for Simple and scalable GNNs (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2021_graph_684,
  title = {{Graph Neural Networks with Heterophily}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/11168-graph-neural-networks-with-heterophily/},
}

@inproceedings{neurips2020_design_59687,
  title = {{Design Space for Graph Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18047},
}

@inproceedings{iclr2021_combining_30043,
  title = {{Combining Label Propagation and Simple Models out-performs Graph Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3274},
}

@inproceedings{iclr2021_how_30350,
  title = {{How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3229},
}

@inproceedings{aaai2020_fast_101943,
  title = {{Fast and Deep Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5803},
}

@inproceedings{aaai2021_sdgnn_1308,
  title = {{SDGNN: Learning Node Representation for Signed Directed Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/00196-sdgnn-learning-node-representation-for-signed-directed-networks/},
}

@inproceedings{iclr2021_adaptive_30617,
  title = {{Adaptive Universal Generalized PageRank Graph Neural Network}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2940},
}

@inproceedings{neurips2020_towards_60986,
  title = {{Towards Deeper Graph Neural Networks with Differentiable Group Normalization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17528},
}

@inproceedings{neurips2022_revisiting_64770,
  title = {{Revisiting Heterophily For Graph Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54959},
}

@inproceedings{neurips2021_federated_63558,
  title = {{Federated Graph Classification over Non-IID Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27233},
}

@inproceedings{neurips2021_labeling_61825,
  title = {{Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28535},
}

@inproceedings{neurips2020_implicit_60046,
  title = {{Implicit Graph Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17508},
}

@inproceedings{neurips2020_scalable_60782,
  title = {{Scalable Graph Neural Networks via Bidirectional Propagation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17220},
}

@inproceedings{aaai2020_gralsp_101999,
  title = {{GraLSP: Graph Neural Networks with Local Structural Patterns}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5861},
}

@inproceedings{neurips2021_neo_61867,
  title = {{Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27695},
}

@inproceedings{cvpr2021_binary_16651,
  title = {{Binary Graph Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{icml2020_gnn_38239,
  title = {{GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5897},
}

@inproceedings{iclr2022_graph_30859,
  title = {{Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6711},
}

@inproceedings{iclr2022_how_31061,
  title = {{How Attentive are Graph Attention Networks?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6366},
}

@inproceedings{aaai2021_one_1107,
  title = {{One-shot Graph Neural Architecture Search with Dynamic Search Space}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08510-one-shot-graph-neural-architecture-search-with-dynamic-search-space/},
}

@inproceedings{aaai2024_dynamic_5770,
  title = {{Dynamic Spiking Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29587},
}

@inproceedings{aaai2025_modality_9976,
  title = {{Modality-Independent Graph Neural Networks with Global Transformers for Multimodal Recommendation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33283},
}

@inproceedings{aaai2024_graph_6157,
  title = {{Graph Neural Networks with Soft Association between Topology and Attribute}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28778},
}

@inproceedings{aaai2024_learning_6511,
  title = {{Learning to Reweight for Generalizable Graph Neural Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28673},
}

@inproceedings{aaai2024_label_6415,
  title = {{Label Attentive Distillation for GNN-Based Graph Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28693},
}

@inproceedings{aaai2024_rethinking_7128,
  title = {{Rethinking Causal Relationships Learning in Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29103},
}

@inproceedings{neurips2024_what_71370,
  title = {{What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95879},
}

@inproceedings{aaai2025_learning_9745,
  title = {{Learning Production Functions for Supply Chains with Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35004},
}

@inproceedings{neurips2024_the_72231,
  title = {{The Intelligible and Effective Graph Neural Additive Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95111},
}

@inproceedings{aaai2025_a_7923,
  title = {{A Scalable and Effective Alternative to Graph Transformers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34231},
}

@inproceedings{aaai2025_grain_9289,
  title = {{GRAIN: Multi-Granular and Implicit Information Aggregation Graph Neural Network for Heterophilous Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33461},
}

@inproceedings{icml2025_can_47735,
  title = {{Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44865},
}

@inproceedings{neurips2024_graph_70250,
  title = {{Graph Classification via Reference Distribution Learning: Theory and Practice}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96839},
}

@inproceedings{aaai2024_improving_6292,
  title = {{Improving Distinguishability of Class for Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29126},
}

@inproceedings{icml2024_graph_44989,
  title = {{Graph Neural Networks Use Graphs When They Shouldn't}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33463},
}

@inproceedings{neurips2024_spiking_72448,
  title = {{Spiking Graph Neural Network on Riemannian Manifolds}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94910},
}

@inproceedings{aaai2024_deep_5641,
  title = {{Deep Learning on Graphs: A Data-Centric Exploration}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30287},
}

@inproceedings{aaai2024_simple_7344,
  title = {{Simple Orthogonal Graph Representation Learning (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30430},
}

@inproceedings{aaai2025_state_10837,
  title = {{State Encodings for GNN-Based Lifted Planners}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34853},
}

@inproceedings{cvpr2025_nn_27045,
  title = {{NN-Former: Rethinking Graph Structure in Neural Architecture Representation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33081},
}