% Key papers for Edge-of-stability dynamics (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2018_visualizing_57773,
  title = {{Visualizing the Loss Landscape of Neural Nets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11618},
}

@inproceedings{icml2018_essentially_36675,
  title = {{Essentially No Barriers in Neural Network Energy Landscape}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2349},
}

@inproceedings{icml2019_an_37153,
  title = {{An Investigation into Neural Net Optimization via Hessian Eigenvalue Density}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4303},
}

@inproceedings{iclr2019_on_29072,
  title = {{On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/875},
}

@inproceedings{neurips2021_gradient_62888,
  title = {{Gradient Starvation: A Learning Proclivity in Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/25974},
}

@inproceedings{neurips2019_explaining_58234,
  title = {{Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14374},
}

@inproceedings{cvpr2022_can_18437,
  title = {{Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent From the Decision Boundary Perspective}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{iclr2020_the_29750,
  title = {{The Break-Even Point on Optimization Trajectories of Deep Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=r1g87C4KwB},
}

@inproceedings{iclr2021_entropic_30754,
  title = {{Entropic gradient descent algorithms and wide flat minima}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2728},
}

@inproceedings{icml2019_understanding_37827,
  title = {{Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3755},
}

@inproceedings{iclr2021_gradient_30571,
  title = {{Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2577},
}

@inproceedings{icml2019_passed_37651,
  title = {{Passed \& Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3706},
}

@inproceedings{icml2023_dropout_41808,
  title = {{Dropout Reduces Underfitting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24356},
}

@inproceedings{neurips2024_why_71871,
  title = {{Why Warmup the Learning Rate? Underlying Mechanisms and Improvements}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95431},
}

@inproceedings{iclr2021_neural_30648,
  title = {{Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2715},
}

@inproceedings{aaai2021_a_12,
  title = {{A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09481-a-deeper-look-at-the-hessian-eigenspectrum-of-deep-neural-networks-and-its-applications-to-regularization/},
}

@inproceedings{icml2021_toward_40037,
  title = {{Toward Better Generalization Bounds with Locally Elastic Stability}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9565},
}

@inproceedings{icml2021_catastrophic_39125,
  title = {{Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8485},
}

@inproceedings{icml2021_how_39435,
  title = {{How to Learn when Data Reacts to Your Model: Performative Gradient Descent}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9355},
}

@inproceedings{iclr2018_stabilizing_28624,
  title = {{Stabilizing Adversarial Nets with Prediction Methods}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/213},
}

@inproceedings{neurips2024_heavy_72286,
  title = {{Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95059},
}

@inproceedings{neurips2024_identifying_72926,
  title = {{Identifying Equivalent Training Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94485},
}

@inproceedings{aaai2024_on_6840,
  title = {{On the Unstable Convergence Regime of Gradient Descent}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29017},
}

@inproceedings{icml2025_the_46965,
  title = {{The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45615},
}

@inproceedings{neurips2024_bias_72092,
  title = {{Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95235},
}

@inproceedings{neurips2024_stepping_72223,
  title = {{Stepping on the Edge: Curvature Aware Learning Rate Tuners}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95119},
}

@inproceedings{neurips2025_non_76009,
  title = {{Non-Singularity of the Gradient Descent Map for Neural Networks with Piecewise Analytic Activations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Ecw0Cina9N},
}

@inproceedings{iclr2025_universal_82386,
  title = {{Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29406},
}

@inproceedings{iclr2024_improving_34199,
  title = {{Improving Convergence and Generalization Using Parameter Symmetries}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18876},
}

@inproceedings{iclr2024_outliers_35091,
  title = {{Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17982},
}

@inproceedings{icml2024_no_43502,
  title = {{No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34950},
}

@inproceedings{icml2024_learning_43669,
  title = {{Learning Associative Memories with Gradient Descent}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34783},
}

@inproceedings{icml2024_deconstructing_43818,
  title = {{Deconstructing the Goldilocks Zone of Neural Network Initialization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34634},
}

@inproceedings{icml2025_understanding_47646,
  title = {{Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44951},
}

@inproceedings{icml2026_gradient_50452,
  title = {{Gradient Descent with Large Step Size Restores Symmetry in Deep Linear Networks with Multi-Pathway}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=CVXqBkLF5y},
}

@inproceedings{icml2026_flatland_51581,
  title = {{Flatland: The Adventures of Gradient Descent with Large Step Sizes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=NpSI4x2vBS},
}

@inproceedings{icml2026_why_52896,
  title = {{Why Do We Need Warm-up? A Theoretical Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=a6fo32UnpU},
}

@inproceedings{icml2026_from_53648,
  title = {{From Flat Facts to Sharp Hallucinations: Detecting Stubborn Errors via Gradient Sensitivity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=hQYbnNccMq},
}

@inproceedings{icml2026_non_54511,
  title = {{Non-Euclidean Gradient Descent Operates at the Edge of Stability}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=piWlEHb4Db},
}