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

@inproceedings{cvpr2023_run_22084,
  title = {{Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22121},
}

@inproceedings{neurips2016_binarized_55603,
  title = {{Binarized Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6910},
}

@inproceedings{icml2017_large_36241,
  title = {{Large-Scale Evolution of Image Classifiers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/634},
}

@inproceedings{cvpr2018_morphnet_13385,
  title = {{MorphNet: Fast \& Simple Resource-Constrained Structure Learning of Deep Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Gordon_MorphNet_Fast__CVPR_2018_paper.html},
}

@inproceedings{iclr2018_training_28508,
  title = {{Training and Inference with Integers in Deep Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/330},
}

@inproceedings{icml2017_device_36148,
  title = {{Device Placement Optimization with Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/888},
}

@inproceedings{cvpr2016_firecaffe_11555,
  title = {{FireCaffe: Near-Linear Acceleration of Deep Neural Network Training on Compute Clusters}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2019_gpipe_58311,
  title = {{GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13257},
}

@inproceedings{cvpr2017_polynet_12540,
  title = {{PolyNet: A Pursuit of Structural Diversity in Very Deep Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2020_resolution_16112,
  title = {{Resolution Adaptive Networks for Efficient Inference}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{icml2020_which_38939,
  title = {{Which Tasks Should Be Learned Together in Multi-task Learning?}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5875},
}

@inproceedings{neurips2017_learned_56409,
  title = {{Learned D-AMP: Principled Neural Network based Compressive Image Recovery}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8967},
}

@inproceedings{neurips2018_learning_57321,
  title = {{Learning to Optimize Tensor Programs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11341},
}

@inproceedings{cvpr2019_focnet_14182,
  title = {{FOCNet: A Fractional Optimal Control Network for Image Denoising}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_regularizing_14723,
  title = {{Regularizing Activation Distribution for Training Binarized Deep Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2021_asymmetric_16609,
  title = {{Asymmetric Gained Deep Image Compression With Continuous Rate Adaptation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{icml2017_adaptive_36053,
  title = {{Adaptive Neural Networks for Efficient Inference}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/807},
}

@inproceedings{cvpr2018_hydranets_13195,
  title = {{HydraNets: Specialized Dynamic Architectures for Efficient Inference}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Mullapudi_HydraNets_Specialized_Dynamic_CVPR_2018_paper.html},
}

@inproceedings{icml2019_on_37597,
  title = {{On The Power of Curriculum Learning in Training Deep Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3720},
}

@inproceedings{aaai2019_snr_99695,
  title = {{SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3788},
}

@inproceedings{aaai2024_model_6662,
  title = {{Model-Driven Deep Neural Network for Enhanced AoA Estimation Using 5G gNB}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27773},
}

@inproceedings{aaai2024_a_5041,
  title = {{A Model for Estimating the Economic Costs of Computer Vision Systems That Use Deep Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30343},
}

@inproceedings{aaai2025_poplar_10325,
  title = {{Poplar: Efficient Scaling of Distributed DNN Training on Heterogeneous GPU Clusters}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34417},
}

@inproceedings{cvpr2024_deep_23132,
  title = {{Deep-TROJ: An Inference Stage Trojan Insertion Algorithm through Efficient Weight Replacement Attack}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31006},
}

@inproceedings{neurips2024_fast_72934,
  title = {{Fast yet Safe: Early-Exiting with Risk Control}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94477},
}

@inproceedings{cvpr2024_1_22609,
  title = {{1-Lipschitz Layers Compared: Memory Speed and Certifiable Robustness}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30332},
}

@inproceedings{neurips2024_activation_72216,
  title = {{Activation Map Compression through Tensor Decomposition for Deep Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95125},
}

@inproceedings{neurips2024_tinytta_72599,
  title = {{TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94778},
}

@inproceedings{icml2024_mechanistic_43943,
  title = {{Mechanistic Design and Scaling of Hybrid Architectures}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34509},
}

@inproceedings{neurips2024_physics_72112,
  title = {{Physics-Constrained Comprehensive Optical Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95217},
}

@inproceedings{neurips2024_a_71756,
  title = {{A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95533},
}

@inproceedings{aaai2024_building_5323,
  title = {{Building Variable-Sized Models via Learngene Pool}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29415},
}

@inproceedings{aaai2024_layer_6431,
  title = {{Layer Compression of Deep Networks with Straight Flows}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29107},
}

@inproceedings{aaai2024_when_7820,
  title = {{When to Grow? A Fitting Risk-Aware Policy for Layer Growing in Deep Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28414},
}

@inproceedings{cvpr2025_meet_26850,
  title = {{MEET: Towards Memory-Efficient Temporal Sparse Deep Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34243},
}

@inproceedings{iclr2024_tensor_33476,
  title = {{Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19599},
}

@inproceedings{neurips2024_comera_73394,
  title = {{CoMERA: Computing- and Memory-Efficient Training via Rank-Adaptive Tensor Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94061},
}

@inproceedings{aaai2024_an_5181,
  title = {{An Empirical Study of Distributed Deep Learning Training on Edge (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30485},
}

@inproceedings{aaai2024_vericompress_7761,
  title = {{VeriCompress: A Tool to Streamline the Synthesis of Verified Robust Compressed Neural Networks from Scratch}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30327},
}

@inproceedings{iclr2024_scaling_34400,
  title = {{Scaling Supervised Local Learning with Augmented Auxiliary Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18675},
}