% Key papers for Compact CNN architectures (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{iclr2021_an_30411,
  title = {{An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3013},
}

@inproceedings{aaai2017_inception_103952,
  title = {{Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11231},
}

@inproceedings{cvpr2016_quantized_11781,
  title = {{Quantized Convolutional Neural Networks for Mobile Devices}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2016_fast_11545,
  title = {{Fast Algorithms for Convolutional Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2022_cmt_18420,
  title = {{CMT: Convolutional Neural Networks Meet Vision Transformers}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2017_designing_12200,
  title = {{Designing Energy-Efficient Convolutional Neural Networks Using Energy-Aware Pruning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2017_deep_56239,
  title = {{Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9336},
}

@inproceedings{neurips2018_dropblock_57070,
  title = {{DropBlock: A regularization method for convolutional networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/12014},
}

@inproceedings{iclr2017_designing_28300,
  title = {{Designing Neural Network Architectures using Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=S1c2cvqee},
}

@inproceedings{cvpr2020_attention_15157,
  title = {{Attention Scaling for Crowd Counting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2018_reversible_102401,
  title = {{Reversible Architectures for Arbitrarily Deep Residual Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11668},
}

@inproceedings{cvpr2020_addernet_15125,
  title = {{AdderNet: Do We Really Need Multiplications in Deep Learning?}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2017_active_12042,
  title = {{Active Convolution: Learning the Shape of Convolution for Image Classification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{aaai2020_icd_103021,
  title = {{ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6331},
}

@inproceedings{cvpr2019_meta_14510,
  title = {{Meta-Learning Convolutional Neural Architectures for Multi-Target Concrete Defect Classification With the COncrete DEfect BRidge IMage Dataset}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{iclr2022_mobilevit_31807,
  title = {{MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6230},
}

@inproceedings{cvpr2020_uncertainty_16395,
  title = {{Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2018_task_57676,
  title = {{Task-Driven Convolutional Recurrent Models of the Visual System}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11517},
}

@inproceedings{cvpr2018_wide_13738,
  title = {{Wide Compression: Tensor Ring Nets}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Wang_Wide_Compression_Tensor_CVPR_2018_paper.html},
}

@inproceedings{neurips2017_learning_56432,
  title = {{Learning Spherical Convolution for Fast Features from 360° Imagery}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8849},
}

@inproceedings{cvpr2024_repvit_24618,
  title = {{RepViT: Revisiting Mobile CNN From ViT Perspective}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29201},
}

@inproceedings{aaai2024_multiscale_6727,
  title = {{Multiscale Low-Frequency Memory Network for Improved Feature Extraction in Convolutional Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28411},
}

@inproceedings{aaai2024_enhancing_5848,
  title = {{Enhancing Healthcare Predictions with Deep Learning Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30543},
}

@inproceedings{iclr2024_fully_34864,
  title = {{Fully Hyperbolic Convolutional Neural Networks for Computer Vision}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18210},
}

@inproceedings{neurips2024_b_72294,
  title = {{B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95051},
}

@inproceedings{icml2024_which_45233,
  title = {{Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33219},
}

@inproceedings{neurips2025_normalize_80082,
  title = {{Normalize Filters! Classical Wisdom for Deep Vision}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=w15atmg0uX},
}

@inproceedings{aaai2026_airwino_106936,
  title = {{AirWino: Optimized Winograd Convolution for Accelerating CNN Inference on ARMv8 Processors}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39288},
}

@inproceedings{iclr2024_matrix_33543,
  title = {{Matrix Manifold Neural Networks++}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19532},
}