% Key papers for Efficient network training and design (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2020_eca_15454,
  title = {{ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_coordinate_16757,
  title = {{Coordinate Attention for Efficient Mobile Network Design}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2023_mobileone_21583,
  title = {{MobileOne: An Improved One Millisecond Mobile Backbone}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22791},
}

@inproceedings{neurips2018_searching_57610,
  title = {{Searching for Efficient Multi-Scale Architectures for Dense Image Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11831},
}

@inproceedings{iclr2019_slimmable_28874,
  title = {{Slimmable Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/796},
}

@inproceedings{cvpr2019_snapshot_14844,
  title = {{Snapshot Distillation: Teacher-Student Optimization in One Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2021_activate_16563,
  title = {{Activate or Not: Learning Customized Activation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_rethinking_17749,
  title = {{Rethinking Channel Dimensions for Efficient Model Design}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{neurips2020_multiscale_60374,
  title = {{Multiscale Deep Equilibrium Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17269},
}

@inproceedings{cvpr2021_condensenet_16733,
  title = {{CondenseNet V2: Sparse Feature Reactivation for Deep Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2018_learning_13301,
  title = {{Learning Strict Identity Mappings in Deep Residual Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Yu_Learning_Strict_Identity_CVPR_2018_paper.html},
}

@inproceedings{cvpr2022_smooth_19897,
  title = {{Smooth Maximum Unit: Smooth Activation Function for Deep Networks Using Smoothing Maximum Technique}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{neurips2019_data_58086,
  title = {{Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14105},
}

@inproceedings{cvpr2023_towards_22364,
  title = {{Towards All-in-One Pre-Training via Maximizing Multi-Modal Mutual Information}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22437},
}

@inproceedings{cvpr2020_what_16482,
  title = {{What Deep CNNs Benefit From Global Covariance Pooling: An Optimization Perspective}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2020_budgeted_29568,
  title = {{Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HyxLRTVKPH},
}

@inproceedings{neurips2020_is_60115,
  title = {{Is normalization indispensable for training deep neural network?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16828},
}

@inproceedings{neurips2020_gradaug_59955,
  title = {{GradAug: A New Regularization Method for Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17960},
}

@inproceedings{iclr2024_moganet_34627,
  title = {{MogaNet: Multi-order Gated Aggregation Network}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18447},
}

@inproceedings{iclr2023_reversible_32503,
  title = {{Reversible Column Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11922},
}

@inproceedings{aaai2024_mca_6565,
  title = {{MCA: Moment Channel Attention Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28035},
}

@inproceedings{aaai2025_dust_8836,
  title = {{Dust-Mamba: An Efficient Dust Storm Detection Network with Multiple Data Sources}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34997},
}

@inproceedings{aaai2025_inheriting_9566,
  title = {{Inheriting Generalized Learngene for Efficient Knowledge Transfer across Multiple Tasks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34473},
}

@inproceedings{neurips2025_gompertz_78302,
  title = {{Gompertz Linear Units: Leveraging Asymmetry for Enhanced Learning Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=d8yAQOSLwv},
}

@inproceedings{neurips2025_mobileode_79776,
  title = {{MobileODE: An Extra Lightweight Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=spjAvoZpVW},
}