% Key papers for Symmetry and equivariance in loss landscapes (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2018_beyond_12866,
  title = {{Beyond the Pixel-Wise Loss for Topology-Aware Delineation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Mosinska_Beyond_the_Pixel-Wise_CVPR_2018_paper.html},
}

@inproceedings{neurips2017_svcca_56641,
  title = {{SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9379},
}

@inproceedings{neurips2018_loss_57347,
  title = {{Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11839},
}

@inproceedings{neurips2022_on_66046,
  title = {{On Embeddings for Numerical Features in Tabular Deep Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54180},
}

@inproceedings{neurips2021_a_61925,
  title = {{A Geometric Analysis of Neural Collapse with Unconstrained Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28099},
}

@inproceedings{aaai2021_riemannian_1284,
  title = {{Riemannian Embedding Banks for Common Spatial Patterns with EEG-based SPD Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/00854-riemannian-embedding-banks-for-common-spatial-patterns-with-eeg-based-spd-neural-networks/},
}

@inproceedings{icml2018_tropical_37064,
  title = {{Tropical Geometry of Deep Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2048},
}

@inproceedings{aaai2021_a_40,
  title = {{A Permutation-Equivariant Neural Network Architecture For Auction Design}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/05664-a-permutation-equivariant-neural-network-architecture-for-auction-design/},
}

@inproceedings{neurips2020_the_60942,
  title = {{The Diversified Ensemble Neural Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16922},
}

@inproceedings{neurips2021_revisiting_62634,
  title = {{Revisiting Model Stitching to Compare Neural Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27797},
}

@inproceedings{neurips2020_pllay_60562,
  title = {{PLLay: Efficient Topological Layer based on Persistent Landscapes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18903},
}

@inproceedings{icml2021_geometry_39390,
  title = {{Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/10331},
}

@inproceedings{iclr2023_repair_32963,
  title = {{REPAIR: REnormalizing Permuted Activations for Interpolation Repair}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/10833},
}

@inproceedings{neurips2018_pca_57497,
  title = {{PCA of high dimensional random walks with comparison to neural network training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11975},
}

@inproceedings{icml2021_principled_39805,
  title = {{Principled Simplicial Neural Networks for Trajectory Prediction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/10021},
}

@inproceedings{neurips2023_geometric_67835,
  title = {{Geometric Algebra Transformer}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71925},
}

@inproceedings{neurips2021_taxonomizing_62123,
  title = {{Taxonomizing local versus global structure in neural network loss landscapes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28104},
}

@inproceedings{neurips2017_deep_56247,
  title = {{Deep Subspace Clustering Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8800},
}

@inproceedings{neurips2022_on_64127,
  title = {{On the Symmetries of Deep Learning Models and their Internal Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53814},
}

@inproceedings{neurips2022_liegg_64167,
  title = {{LieGG: Studying Learned Lie Group Generators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52806},
}

@inproceedings{icml2024_position_43863,
  title = {{Position: Categorical Deep Learning is an Algebraic Theory of All Architectures}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34589},
}

@inproceedings{neurips2024_universal_72510,
  title = {{Universal Neural Functionals}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94854},
}

@inproceedings{neurips2024_the_72562,
  title = {{The Prevalence of Neural Collapse in Neural Multivariate Regression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94810},
}

@inproceedings{aaai2025_a_7920,
  title = {{A Renormalization Group Framework for Scale-Invariant Feature Learning in Deep Neural Networks (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35269},
}

@inproceedings{cvpr2024_deciphering_23121,
  title = {{Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30168},
}

@inproceedings{icml2025_incorporating_47708,
  title = {{Incorporating Arbitrary Matrix Group Equivariance into KANs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44891},
}

@inproceedings{neurips2024_exploring_74150,
  title = {{Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93392},
}

@inproceedings{neurips2025_generalized_76586,
  title = {{Generalized Linear Mode Connectivity for Transformers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=KurYdcCbjv},
}

@inproceedings{neurips2025_a_79618,
  title = {{A Tale of Two Symmetries: Exploring the Loss Landscape of Equivariant Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=rH4aGTL4jY},
}

@inproceedings{iclr2026_tversky_88255,
  title = {{Tversky Neural Networks: Psychologically Plausible Deep Learning with Differentiable Tversky Similarity}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=koKWoKaMrE},
}

@inproceedings{aaai2025_deep_8683,
  title = {{Deep-Union Completion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33702},
}

@inproceedings{iclr2024_polynomial_33547,
  title = {{Polynomial Width is Sufficient for Set Representation with High-dimensional Features}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19528},
}

@inproceedings{icml2024_tilt_43503,
  title = {{Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34949},
}

@inproceedings{icml2024_geomformer_44667,
  title = {{GeoMFormer: A General Architecture for Geometric Molecular Representation Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33785},
}

@inproceedings{icml2024_harmony_45055,
  title = {{Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33397},
}

@inproceedings{icml2024_equivariant_45319,
  title = {{Equivariant Deep Weight Space Alignment}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33133},
}

@inproceedings{icml2024_emergent_45424,
  title = {{Emergent Equivariance in Deep Ensembles}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33027},
}

@inproceedings{icml2025_understanding_46600,
  title = {{Understanding Mode Connectivity via Parameter Space Symmetry}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45969},
}

@inproceedings{icml2026_beyond_50745,
  title = {{Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=FJLz8swPpd},
}

@inproceedings{icml2026_do_51683,
  title = {{Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=OnmYXKZ6oa},
}