% Key papers for Spectral GNN design (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2022_convolutional_65781,
  title = {{Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54348},
}

@inproceedings{neurips2019_stability_59010,
  title = {{Stability of Graph Scattering Transforms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13878},
}

@inproceedings{neurips2021_bernnet_62409,
  title = {{BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27607},
}

@inproceedings{iclr2023_sign_32553,
  title = {{Sign and Basis Invariant Networks for Spectral Graph Representation Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11795},
}

@inproceedings{aaai2023_signed_4689,
  title = {{Signed Laplacian Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25565},
}

@inproceedings{iclr2023_specformer_31924,
  title = {{Specformer: Spectral Graph Neural Networks Meet Transformers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/10782},
}

@inproceedings{neurips2019_dfnets_58078,
  title = {{DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13720},
}

@inproceedings{aaai2024_improving_6293,
  title = {{Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29326},
}

@inproceedings{iclr2021_isometric_30140,
  title = {{Isometric Transformation Invariant and Equivariant Graph Convolutional Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3192},
}

@inproceedings{icml2021_interpretable_39477,
  title = {{Interpretable Stability Bounds for Spectral Graph Filters}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/10145},
}

@inproceedings{neurips2024_unifying_74293,
  title = {{Unifying Homophily and Heterophily for Spectral Graph Neural Networks via Triple Filter Ensembles}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93265},
}

@inproceedings{aaai2024_wavenet_7788,
  title = {{WaveNet: Tackling Non-stationary Graph Signals via Graph Spectral Wavelets}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28781},
}

@inproceedings{icml2024_how_44705,
  title = {{How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33747},
}

@inproceedings{neurips2020_on_60493,
  title = {{On the equivalence of molecular graph convolution and molecular wave function with poor basis set}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16836},
}

@inproceedings{iclr2024_holonets_33978,
  title = {{HoloNets: Spectral Convolutions do extend to Directed Graphs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19097},
}

@inproceedings{icml2025_a_47477,
  title = {{A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45116},
}

@inproceedings{neurips2022_graph_66061,
  title = {{Graph Scattering beyond Wavelet Shackles}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55100},
}

@inproceedings{aaai2025_asymmetric_8155,
  title = {{Asymmetric Learning for Spectral Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34069},
}

@inproceedings{icml2025_grokformer_48993,
  title = {{GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43630},
}

@inproceedings{neurips2023_equivariant_67435,
  title = {{Equivariant Neural Operator Learning with Graphon Convolution}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72298},
}

@inproceedings{neurips2024_equivariant_74543,
  title = {{Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93041},
}

@inproceedings{iclr2025_joint_84142,
  title = {{Joint Graph Rewiring and Feature Denoising via Spectral Resonance}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27686},
}

@inproceedings{icml2026_l2g_53938,
  title = {{L2G-NET: Local to Global Spectral Graph Neural Networks via Cauchy Factorizations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=kD8iJmyn5l},
}

@inproceedings{neurips2025_herofilter_75346,
  title = {{HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=77Kw7b7EYb},
}

@inproceedings{neurips2025_you_77531,
  title = {{You Only Spectralize Once: Taking a Spectral Detour to Accelerate Graph Neural Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=UxzfzqgnpZ},
}

@inproceedings{iclr2026_lightweight_89540,
  title = {{Lightweight Transformer for EEG Classification via Balanced Signed Graph Algorithm Unrolling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=zxsLio384j},
}

@inproceedings{neurips2026_spectral_90995,
  title = {{Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149066},
}

@inproceedings{neurips2026_gist_91818,
  title = {{GIST: Gauge-Invariant Spectral Transformers for Scalable Graph Neural Operators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152787},
}

@inproceedings{aaai2026_deloopsgnn_107099,
  title = {{DeloopSGNN: Revisiting Spectral GNNs Through the Lens of Spatial Aggregation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39451},
}

@inproceedings{icml2024_slog_43252,
  title = {{SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35200},
}

@inproceedings{icml2024_unsupervised_45716,
  title = {{Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32736},
}

@inproceedings{icml2025_position_46903,
  title = {{Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/40152},
}