% Key papers for Differentiating through embedded optimization (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2017_learning_36271,
  title = {{Learning to Learn without Gradient Descent by Gradient Descent}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/687},
}

@inproceedings{neurips2016_the_56042,
  title = {{The Parallel Knowledge Gradient Method for Batch Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7179},
}

@inproceedings{iclr2019_stochastic_28860,
  title = {{Stochastic Optimization of Sorting Networks via Continuous Relaxations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/920},
}

@inproceedings{icml2019_adaptive_37137,
  title = {{Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4048},
}

@inproceedings{cvpr2018_ds_12945,
  title = {{DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Bernard_DS_Tighter_Lifting-Free_CVPR_2018_paper.html},
}

@inproceedings{cvpr2016_sublabel_11901,
  title = {{Sublabel-Accurate Relaxation of Nonconvex Energies}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2016_regularized_55960,
  title = {{Regularized Nonlinear Acceleration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7410},
}

@inproceedings{neurips2016_coordinate_55652,
  title = {{Coordinate-wise Power Method}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7381},
}

@inproceedings{neurips2016_cyclades_55657,
  title = {{Cyclades: Conflict-free Asynchronous Machine Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7326},
}

@inproceedings{neurips2019_trivializations_59121,
  title = {{Trivializations for Gradient-Based Optimization on Manifolds}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13957},
}

@inproceedings{cvpr2020_auto_15169,
  title = {{Auto-Tuning Structured Light by Optical Stochastic Gradient Descent}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{icml2019_guided_37417,
  title = {{Guided evolutionary strategies: augmenting random search with surrogate gradients}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3975},
}

@inproceedings{neurips2018_houdini_57194,
  title = {{HOUDINI: Lifelong Learning as Program Synthesis}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11830},
}

@inproceedings{neurips2019_a_57813,
  title = {{A Kernel Loss for Solving the Bellman Equation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14441},
}

@inproceedings{aaai2021_on_1101,
  title = {{On the Verification of Neural ODEs with Stochastic Guarantees}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/11525-on-the-verification-of-neural-odes-with-stochastic-guarantees/},
}

@inproceedings{aaai2022_coordinating_1891,
  title = {{Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/05219-coordinating-followers-to-reach-better-equilibria-end-to-end-gradient-descent-for-stackelberg-games/},
}

@inproceedings{neurips2021_practical_62589,
  title = {{Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27163},
}

@inproceedings{cvpr2020_cogradient_15257,
  title = {{Cogradient Descent for Bilinear Optimization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2017_scalable_56654,
  title = {{Scalable Planning with Tensorflow for Hybrid Nonlinear Domains}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9398},
}

@inproceedings{neurips2017_stochastic_56691,
  title = {{Stochastic Submodular Maximization: The Case of Coverage Functions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9452},
}

@inproceedings{neurips2024_gradient_72573,
  title = {{Gradient Guidance for Diffusion Models: An Optimization Perspective}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94799},
}

@inproceedings{neurips2024_minimizing_70510,
  title = {{Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96598},
}

@inproceedings{neurips2024_torchopt_70850,
  title = {{TorchOpt: An Efficient Library for Differentiable Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/98326},
}

@inproceedings{aaai2025_neural_10102,
  title = {{Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34870},
}

@inproceedings{cvpr2024_towards_25059,
  title = {{Towards Robust Learning to Optimize with Theoretical Guarantees}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30663},
}

@inproceedings{iclr2024_domain_34102,
  title = {{Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18973},
}

@inproceedings{aaai2024_accelerating_5112,
  title = {{Accelerating Cutting-Plane Algorithms via Reinforcement Learning Surrogates}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30067},
}

@inproceedings{neurips2025_camo_75582,
  title = {{CAMO: Convergence-Aware Multi-Fidelity Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=9jONuWKoLj},
}

@inproceedings{neurips2025_enhanced_78369,
  title = {{Enhanced Cyclic Coordinate Descent Methods for Elastic Net Penalized Linear Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=duunKHvWKz},
}

@inproceedings{neurips2025_fsnet_79395,
  title = {{FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=oum1txoy1D},
}

@inproceedings{iclr2024_stabilizing_34752,
  title = {{Stabilizing Backpropagation Through Time to Learn Complex Physics}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18322},
}

@inproceedings{icml2024_on_43314,
  title = {{On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35138},
}

@inproceedings{icml2024_dynamic_43743,
  title = {{Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34709},
}

@inproceedings{icml2024_from_43947,
  title = {{From Inverse Optimization to Feasibility to ERM}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34505},
}

@inproceedings{icml2024_lpgd_44485,
  title = {{LPGD: A General Framework for Backpropagation through Embedded Optimization Layers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33967},
}

@inproceedings{icml2025_efficient_46323,
  title = {{Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold Method}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46238},
}

@inproceedings{icml2025_accelerating_46983,
  title = {{Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45599},
}

@inproceedings{icml2025_a_47220,
  title = {{A Generalization Result for Convergence in Learning-to-Optimize}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45367},
}

@inproceedings{icml2025_differentiable_47799,
  title = {{Differentiable Quadratic Optimization For the Maximum Independent Set Problem}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44801},
}

@inproceedings{icml2025_quantum_48920,
  title = {{Quantum Optimization via Gradient-Based Hamiltonian Descent}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43703},
}