% Key papers for Filter design and trained-filter analysis (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_densely_12196,
  title = {{Densely Connected Convolutional Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2016_netvlad_11726,
  title = {{NetVLAD: CNN Architecture for Weakly Supervised Place Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2021_mlp_61694,
  title = {{MLP-Mixer: An all-MLP Architecture for Vision}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28720},
}

@inproceedings{cvpr2018_interpretable_13233,
  title = {{Interpretable Convolutional Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Zhang_Interpretable_Convolutional_Neural_CVPR_2018_paper.html},
}

@inproceedings{cvpr2017_convolutional_12129,
  title = {{Convolutional Neural Network Architecture for Geometric Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2018_gather_57154,
  title = {{Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11895},
}

@inproceedings{cvpr2016_recursive_11807,
  title = {{Recursive Recurrent Nets With Attention Modeling for OCR in the Wild}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2016_dynamic_55695,
  title = {{Dynamic Filter Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6931},
}

@inproceedings{cvpr2016_shallow_11855,
  title = {{Shallow and Deep Convolutional Networks for Saliency Prediction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2018_learning_13270,
  title = {{Learning Convolutional Networks for Content-Weighted Image Compression}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Li_Learning_Convolutional_Networks_CVPR_2018_paper.html},
}

@inproceedings{neurips2017_towards_56732,
  title = {{Towards Accurate Binary Convolutional Neural Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8831},
}

@inproceedings{cvpr2016_image_11603,
  title = {{Image Question Answering Using Convolutional Neural Network With Dynamic Parameter Prediction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2016_monocular_11706,
  title = {{Monocular Depth Estimation Using Neural Regression Forest}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2018_structured_13619,
  title = {{Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Xu_Structured_Attention_Guided_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_adcrowdnet_13803,
  title = {{ADCrowdNet: An Attention-Injective Deformable Convolutional Network for Crowd Understanding}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2017_attentional_12072,
  title = {{Attentional Correlation Filter Network for Adaptive Visual Tracking}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2018_crowd_12938,
  title = {{Crowd Counting With Deep Negative Correlation Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Shi_Crowd_Counting_With_CVPR_2018_paper.html},
}

@inproceedings{cvpr2018_memory_13367,
  title = {{Memory Matching Networks for One-Shot Image Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Cai_Memory_Matching_Networks_CVPR_2018_paper.html},
}

@inproceedings{cvpr2017_local_12436,
  title = {{Local Binary Convolutional Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2017_working_56777,
  title = {{Working hard to know your neighbor's margins: Local descriptor learning loss}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9259},
}

@inproceedings{cvpr2024_comparing_23002,
  title = {{Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30580},
}

@inproceedings{aaai2024_picnn_6893,
  title = {{PICNN: A Pathway towards Interpretable Convolutional Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27971},
}

@inproceedings{neurips2024_interpretable_73412,
  title = {{Interpretable Image Classification with Adaptive Prototype-based Vision Transformers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94047},
}

@inproceedings{aaai2024_nesyfold_6751,
  title = {{NeSyFOLD: A Framework for Interpretable Image Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28235},
}

@inproceedings{neurips2025_imagenet_78760,
  title = {{ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=i5WnXNjwbR},
}

@inproceedings{neurips2025_tv_78236,
  title = {{TV-Rec: Time-Variant Convolutional Filter for Sequential Recommendation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=cWEssTIwG5},
}

@inproceedings{aaai2025_the_10981,
  title = {{The Master Key Filters Hypothesis: Deep Filters Are General}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32175},
}

@inproceedings{neurips2024_model_73860,
  title = {{Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93649},
}

@inproceedings{aaai2025_beyond_8255,
  title = {{Beyond Skip Connection: Pooling and Unpooling Design for Elimination Singularities}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34278},
}

@inproceedings{iclr2024_unveiling_33614,
  title = {{Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19461},
}

@inproceedings{icml2026_a_50850,
  title = {{A Theory of Contrastive Learning with Natural Images}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=GJkayj4SjS},
}

@inproceedings{icml2026_an_50882,
  title = {{An analytic theory of convolutional neural network inverse problems solvers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=GdiPMYeFoG},
}

@inproceedings{neurips2025_msf_78521,
  title = {{msf-CNN: Patch-based Multi-Stage Fusion with Convolutional Neural Networks for TinyML}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=fgW3IZzxmE},
}

@inproceedings{neurips2025_structured_78539,
  title = {{Structured Initialization for Vision Transformers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=fmQFCXAe4v},
}

@inproceedings{neurips2025_the_79097,
  title = {{The Quest for Universal Master Key Filters in DS-CNNs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=lYnNzmFt7r},
}

@inproceedings{neurips2025_convolution_79902,
  title = {{Convolution Goes Higher-Order: A Biologically Inspired Mechanism Empowers Image Classification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=u3aRwVkBv1},
}

@inproceedings{iclr2025_revisiting_81171,
  title = {{Revisiting Convolution Architecture in the Realm of DNA Foundation Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30599},
}

@inproceedings{cvpr2026_fbta_96217,
  title = {{FBTA: Enabling Single-GPU End-to-End Gigapixel WSI Classification with Feature Bridging and Translation Alignment}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Dong_FBTA_Enabling_Single-GPU_End-to-End_Gigapixel_WSI_Classification_with_Feature_Bridging_CVPR_2026_paper.html},
}