% Key papers for Geometry of low-rank and SPD structure (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2017_practical_36342,
  title = {{Practical Gauss-Newton Optimisation for Deep Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/789},
}

@inproceedings{icml2017_geometry_36204,
  title = {{Geometry of Neural Network Loss Surfaces via Random Matrix Theory}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/655},
}

@inproceedings{icml2018_deep_36622,
  title = {{Deep Models of Interactions Across Sets}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2428},
}

@inproceedings{neurips2018_deep_57009,
  title = {{Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11055},
}

@inproceedings{neurips2020_implicit_60050,
  title = {{Implicit Regularization in Deep Learning May Not Be Explainable by Norms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17219},
}

@inproceedings{icml2021_a_38974,
  title = {{A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9727},
}

@inproceedings{neurips2020_practical_60597,
  title = {{Practical Low-Rank Communication Compression in Decentralized Deep Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17626},
}

@inproceedings{icml2017_theoretical_36430,
  title = {{Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/832},
}

@inproceedings{icml2020_random_38670,
  title = {{Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5888},
}

@inproceedings{icml2016_analysis_35737,
  title = {{Analysis of Deep Neural Networks with Extended Data Jacobian Matrix}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/wanga16.html},
}

@inproceedings{iclr2019_learning_29100,
  title = {{Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/702},
}

@inproceedings{icml2021_dropout_39272,
  title = {{Dropout: Explicit Forms and Capacity Control}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/10381},
}

@inproceedings{cvpr2017_hardware_12328,
  title = {{Hardware-Efficient Guided Image Filtering for Multi-Label Problem}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2018_a_56814,
  title = {{A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11848},
}

@inproceedings{neurips2019_learning_58494,
  title = {{Learning Neural Networks with Adaptive Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14128},
}

@inproceedings{cvpr2025_learning_26764,
  title = {{Learning to Normalize on the SPD Manifold under Bures-Wasserstein Geometry}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32514},
}

@inproceedings{icml2020_learning_38377,
  title = {{Learning Factorized Weight Matrix for Joint Filtering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5833},
}

@inproceedings{neurips2021_hessian_63152,
  title = {{Hessian Eigenspectra of More Realistic Nonlinear Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27972},
}

@inproceedings{neurips2020_matrix_60293,
  title = {{Matrix Inference and Estimation in Multi-Layer Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18362},
}

@inproceedings{neurips2024_trade_72314,
  title = {{Trade-Offs of Diagonal Fisher Information Matrix Estimators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95032},
}

@inproceedings{neurips2024_nuclear_73178,
  title = {{Nuclear Norm Regularization for Deep Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94255},
}

@inproceedings{aaai2025_layered_9715,
  title = {{Layered-Parameter Perturbation for Zeroth-Order Optimization of Optical Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34235},
}

@inproceedings{iclr2025_understanding_83546,
  title = {{Understanding Matrix Function Normalizations in Covariance Pooling through the Lens of Riemannian Geometry}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28270},
}

@inproceedings{aaai2025_on_10185,
  title = {{On the Trainability and Classical Simulability of Learning Matrix Product States Variationally}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33701},
}

@inproceedings{icml2024_robustness_43971,
  title = {{Robustness of Nonlinear Representation Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34481},
}

@inproceedings{icml2024_operator_45449,
  title = {{Operator SVD with Neural Networks via Nested Low-Rank Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33002},
}

@inproceedings{icml2025_compact_48624,
  title = {{Compact Matrix Quantum Group Equivariant Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43997},
}

@inproceedings{icml2025_models_48714,
  title = {{Models of Heavy-Tailed Mechanistic Universality}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43908},
}

@inproceedings{icml2026_why_49467,
  title = {{Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=2kSBDoP1rE},
}

@inproceedings{icml2026_deep_52037,
  title = {{Deep Single-Index Fréchet Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=SCjiMmzyFA},
}

@inproceedings{icml2026_kromhc_52164,
  title = {{KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=TI7Q2o6EIa},
}

@inproceedings{icml2026_prism_53710,
  title = {{PRISM: Distribution-free Adaptive Computation of Matrix Functions for Accelerating Neural Network Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=hwhvjhXC0m},
}

@inproceedings{icml2026_on_55170,
  title = {{On the Effect of Misspecifying the Embedding Dimension in Low-rank Network Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=wIMGGV9l1i},
}

@inproceedings{neurips2025_the_76717,
  title = {{The Nuclear Route: Sharp Asymptotics of ERM in Overparameterized Quadratic Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=MNqBFIGT8l},
}

@inproceedings{neurips2025_towards_79111,
  title = {{Towards a General Attention Framework on Gyrovector Spaces for Matrix Manifolds}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=lovTDtbsdZ},
}

@inproceedings{iclr2025_neural_82719,
  title = {{Neural networks on Symmetric Spaces of Noncompact Type}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29080},
}

@inproceedings{iclr2026_fast_84687,
  title = {{Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=5S8ruWKe8l},
}

@inproceedings{iclr2026_the_89392,
  title = {{The Polar Express: Optimal Matrix Sign Methods and their Application to the Muon Algorithm}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=yRtgZ1K8hO},
}