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

@inproceedings{icml2016_group_35859,
  title = {{Group Equivariant Convolutional Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/cohenc16.html},
}

@inproceedings{cvpr2017_deep_12159,
  title = {{Deep Learning on Lie Groups for Skeleton-Based Action Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{icml2020_attentive_37951,
  title = {{Attentive Group Equivariant Convolutional Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6467},
}

@inproceedings{neurips2019_a_57807,
  title = {{A General Theory of Equivariant CNNs on Homogeneous Spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13956},
}

@inproceedings{iclr2020_b_29409,
  title = {{B-Spline CNNs on Lie groups}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=H1gBhkBFDH},
}

@inproceedings{icml2020_universal_38907,
  title = {{Universal Equivariant Multilayer Perceptrons}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6245},
}

@inproceedings{neurips2021_efficient_61295,
  title = {{Efficient Equivariant Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27385},
}

@inproceedings{icml2019_learning_37500,
  title = {{Learning to Convolve: A Generalized Weight-Tying Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3761},
}

@inproceedings{neurips2022_learning_66034,
  title = {{Learning Partial Equivariances From Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53339},
}

@inproceedings{neurips2022_universality_65565,
  title = {{Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54282},
}

@inproceedings{neurips2023_a_69323,
  title = {{A General Framework for Robust G-Invariance in G-Equivariant Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70578},
}

@inproceedings{icml2022_exploiting_40522,
  title = {{Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17825},
}

@inproceedings{icml2022_implicit_40674,
  title = {{Implicit Bias of Linear Equivariant Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16543},
}

@inproceedings{neurips2024_the_73660,
  title = {{The Selective \$G\$-Bispectrum and its Inversion: Applications to \$G\$-Invariant Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93832},
}

@inproceedings{neurips2025_on_77841,
  title = {{On the VC dimension of deep group convolutional neural networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Y9nxhKcgAA},
}

@inproceedings{iclr2025_towards_81036,
  title = {{Towards a Unified and Verified Understanding of Group-Operation Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30732},
}

@inproceedings{iclr2025_learning_81611,
  title = {{Learning Color Equivariant Representations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30166},
}

@inproceedings{iclr2025_group_83689,
  title = {{Group Downsampling with Equivariant Anti-aliasing}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28130},
}

@inproceedings{neurips2026_texttt_93418,
  title = {{\$textttbispectrum\$: Selective \$G\$-Bispectra Made Practical}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/148783},
}