% Key papers for Steerable rotation-equivariant CNNs (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_harmonic_12329,
  title = {{Harmonic Networks: Deep Translation and Rotation Equivariance}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2018_learning_13300,
  title = {{Learning Steerable Filters for Rotation Equivariant CNNs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Weiler_Learning_Steerable_Filters_CVPR_2018_paper.html},
}

@inproceedings{icml2016_exploiting_35828,
  title = {{Exploiting Cyclic Symmetry in Convolutional Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/dieleman16.html},
}

@inproceedings{iclr2018_spherical_28540,
  title = {{Spherical CNNs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/144},
}

@inproceedings{neurips2019_general_58316,
  title = {{General E(2)-Equivariant Steerable CNNs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14355},
}

@inproceedings{neurips2019_deep_58107,
  title = {{Deep Scale-spaces: Equivariance Over Scale}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13824},
}

@inproceedings{iclr2020_scale_29465,
  title = {{Scale-Equivariant Steerable Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HJgpugrKPS},
}

@inproceedings{icml2020_generalizing_38248,
  title = {{Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6320},
}

@inproceedings{neurips2018_clebsch_56941,
  title = {{Clebsch–Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11959},
}

@inproceedings{iclr2018_polar_28549,
  title = {{Polar Transformer Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/263},
}

@inproceedings{iclr2019_a_28867,
  title = {{A rotation-equivariant convolutional neural network model of primary visual cortex}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/922},
}

@inproceedings{icml2017_warped_36454,
  title = {{Warped Convolutions: Efficient Invariance to Spatial Transformations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/660},
}

@inproceedings{iclr2017_steerable_28362,
  title = {{Steerable CNNs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=rJQKYt5ll},
}

@inproceedings{aaai2021_pdo_1138,
  title = {{PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09585-pdo-es2cnns-partial-differential-operator-based-equivariant-spherical-cnns/},
}

@inproceedings{iclr2019_rotdcf_28876,
  title = {{RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/1053},
}

@inproceedings{iclr2018_hexaconv_28666,
  title = {{HexaConv}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/77},
}

@inproceedings{neurips2020_spin_60860,
  title = {{Spin-Weighted Spherical CNNs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18698},
}

@inproceedings{cvpr2024_making_24103,
  title = {{Making Vision Transformers Truly Shift-Equivariant}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29530},
}

@inproceedings{iclr2022_scattering_31467,
  title = {{Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6521},
}

@inproceedings{icml2023_scaling_41968,
  title = {{Scaling Spherical CNNs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24521},
}

@inproceedings{cvpr2025_rotation_27487,
  title = {{Rotation-Equivariant Self-Supervised Method in Image Denoising}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33832},
}

@inproceedings{icml2024_a_43419,
  title = {{A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35033},
}

@inproceedings{icml2024_clifford_44629,
  title = {{Clifford-Steerable Convolutional Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33823},
}

@inproceedings{icml2026_revit_54218,
  title = {{REViT: Roto-reflection Equivariant Convolutional Vision Transformer}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=n2RIMdIbv6},
}

@inproceedings{iclr2026_designing_87807,
  title = {{Designing Affine-Invariant Neural Networks for Photometric Corruption Robustness and Generalization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=fhEwTOLYNZ},
}

@inproceedings{iclr2026_sonic_88713,
  title = {{SONIC: Spectral Oriented Neural Invariant Convolutions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=qDGiMrUVmc},
}

@inproceedings{neurips2026_selective_93415,
  title = {{Selective Disk Bispectrum: A Complete and Rotation Invariant Image Descriptor}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151621},
}

@inproceedings{cvpr2026_unified_98699,
  title = {{Unified Spherical Frontend: Learning Rotation-Equivariant Representations of Spherical Images from Any Camera}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Yu_Unified_Spherical_Frontend_Learning_Rotation-Equivariant_Representations_of_Spherical_Images_from_CVPR_2026_paper.html},
}