% Key papers for Constrained and non-backprop training (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_gans_56332,
  title = {{GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9431},
}

@inproceedings{neurips2019_deep_58099,
  title = {{Deep Leakage from Gradients}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14387},
}

@inproceedings{icml2018_which_37084,
  title = {{Which Training Methods for GANs do actually Converge?}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1900},
}

@inproceedings{cvpr2022_deep_18612,
  title = {{Deep Generalized Unfolding Networks for Image Restoration}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2021_deep_16818,
  title = {{Deep Gradient Projection Networks for Pan-sharpening}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{neurips2017_the_56720,
  title = {{The Numerics of GANs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8972},
}

@inproceedings{icml2017_on_36320,
  title = {{On orthogonality and learning recurrent networks with long term dependencies}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/740},
}

@inproceedings{aaai2018_deeptype_105948,
  title = {{DeepType: Multilingual Entity Linking by Neural Type System Evolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/12008},
}

@inproceedings{icml2016_training_36018,
  title = {{Training Neural Networks Without Gradients: A Scalable ADMM Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/taylor16.html},
}

@inproceedings{neurips2019_differentiable_58127,
  title = {{Differentiable Convex Optimization Layers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13991},
}

@inproceedings{neurips2020_estimating_59799,
  title = {{Estimating Training Data Influence by Tracing Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17789},
}

@inproceedings{neurips2021_differentiable_61802,
  title = {{Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27537},
}

@inproceedings{icml2016_noisy_35919,
  title = {{Noisy Activation Functions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/gulcehre16.html},
}

@inproceedings{neurips2020_just_60121,
  title = {{Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18458},
}

@inproceedings{neurips2019_full_58300,
  title = {{Full-Gradient Representation for Neural Network Visualization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13571},
}

@inproceedings{neurips2017_gradient_56350,
  title = {{Gradient descent GAN optimization is locally stable}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9333},
}

@inproceedings{iclr2018_deep_28603,
  title = {{Deep Learning with Logged Bandit Feedback}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/282},
}

@inproceedings{icml2017_failures_36187,
  title = {{Failures of Gradient-Based Deep Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/694},
}

@inproceedings{icml2018_decoupled_36616,
  title = {{Decoupled Parallel Backpropagation with Convergence Guarantee}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2106},
}

@inproceedings{icml2020_sigua_38721,
  title = {{SIGUA: Forgetting May Make Learning with Noisy Labels More Robust}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5866},
}

@inproceedings{aaai2024_eg_5780,
  title = {{EG-NAS: Neural Architecture Search with Fast Evolutionary Exploration}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28993},
}

@inproceedings{aaai2024_qlabgrad_7035,
  title = {{QLABGrad: A Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29095},
}

@inproceedings{neurips2024_dual_73336,
  title = {{Dual Cone Gradient Descent for Training Physics-Informed Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94109},
}

@inproceedings{aaai2024_sdgmnet_7215,
  title = {{SDGMNet: Statistic-Based Dynamic Gradient Modulation for Local Descriptor Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27916},
}

@inproceedings{aaai2024_exponential_5926,
  title = {{Exponential Hardness of Optimization from the Locality in Quantum Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29614},
}

@inproceedings{aaai2024_one_6846,
  title = {{One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29336},
}

@inproceedings{cvpr2025_towards_27927,
  title = {{Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34469},
}

@inproceedings{iclr2024_synaptic_35604,
  title = {{Synaptic Weight Distributions Depend on the Geometry of Plasticity}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17469},
}

@inproceedings{neurips2024_loss_73342,
  title = {{Loss Landscape Characterization of Neural Networks without Over-Parametrization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94103},
}

@inproceedings{cvpr2024_from_23524,
  title = {{From Variance to Veracity: Unbundling and Mitigating Gradient Variance in Differentiable Bundle Adjustment Layers}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31135},
}

@inproceedings{iclr2024_magnitude_34883,
  title = {{Magnitude Invariant Parametrizations Improve Hypernetwork Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18191},
}

@inproceedings{iclr2025_mothernet_80868,
  title = {{MotherNet: Fast Training and Inference via Hyper-Network Transformers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30899},
}

@inproceedings{aaai2025_fast_9151,
  title = {{Fast and Slow Gradient Approximation for Binary Neural Network Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34896},
}

@inproceedings{aaai2025_improving_9526,
  title = {{Improving Deep Learning Speed and Performance Through Synaptic Neural Balance}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33683},
}

@inproceedings{icml2026_mitigating_50785,
  title = {{Mitigating Gradient Pathology in PINNs through Aligned Constraint}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Fisw2kc7EY},
}

@inproceedings{icml2026_surge_51524,
  title = {{SURGE: Surrogate Gradient Adaptation in Binary Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=NAkeQ3C4tn},
}

@inproceedings{icml2026_high_53021,
  title = {{High-Dimensional Learning Dynamics of Quantized Models with Straight-Through Estimator}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=bI9moH3UZw},
}

@inproceedings{neurips2024_cronos_72705,
  title = {{CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94682},
}

@inproceedings{neurips2025_deep_74730,
  title = {{Deep Legendre Transform}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=0YUHjKjjUY},
}

@inproceedings{neurips2025_asymptotically_74890,
  title = {{Asymptotically Stable Quaternion-valued Hopfield-structured Neural Network with Periodic Projection-based Supervised Learning Rules}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=2FmTcj6WMB},
}