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

@inproceedings{cvpr2019_selective_14787,
  title = {{Selective Kernel Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2020_dynamic_15444,
  title = {{Dynamic Convolution: Attention Over Convolution Kernels}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2016_fast_11547,
  title = {{Fast ConvNets Using Group-Wise Brain Damage}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2019_pixel_14644,
  title = {{Pixel-Adaptive Convolutional Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{neurips2019_condconv_58025,
  title = {{CondConv: Conditionally Parameterized Convolutions for Efficient Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13351},
}

@inproceedings{cvpr2020_rethinking_16117,
  title = {{Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_orthogonal_16000,
  title = {{Orthogonal Convolutional Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2022_omni_31037,
  title = {{Omni-Dimensional Dynamic Convolution}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6455},
}

@inproceedings{cvpr2020_dynamic_15445,
  title = {{Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_dynamic_16922,
  title = {{Dynamic Region-Aware Convolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2018_interleaved_13231,
  title = {{Interleaved Structured Sparse 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/Xie_Interleaved_Structured_Sparse_CVPR_2018_paper.html},
}

@inproceedings{cvpr2025_frequency_26322,
  title = {{Frequency Dynamic Convolution for Dense Image Prediction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33112},
}

@inproceedings{cvpr2024_pelk_24445,
  title = {{PeLK: Parameter-efficient Large Kernel ConvNets with Peripheral Convolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31833},
}

@inproceedings{cvpr2022_scaling_19796,
  title = {{Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2022_repmlpnet_19709,
  title = {{RepMLPNet: Hierarchical Vision MLP With Re-Parameterized Locality}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2017_learning_12389,
  title = {{Learning Adaptive Receptive Fields for Deep Image Parsing Network}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{iclr2019_spherical_28806,
  title = {{Spherical CNNs on Unstructured Grids}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/708},
}

@inproceedings{aaai2019_super_101649,
  title = {{Super Sparse Convolutional Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4356},
}

@inproceedings{neurips2019_convolution_58049,
  title = {{Convolution with even-sized kernels and symmetric padding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13342},
}

@inproceedings{cvpr2019_kervolutional_14354,
  title = {{Kervolutional Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2025_shiftwiseconv_27660,
  title = {{ShiftwiseConv: Small Convolutional Kernel with Large Kernel Effect}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34598},
}

@inproceedings{icml2024_kernelwarehouse_43260,
  title = {{KernelWarehouse: Rethinking the Design of Dynamic Convolution}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35192},
}

@inproceedings{icml2024_revealing_45511,
  title = {{Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32941},
}

@inproceedings{neurips2025_pleiades_75616,
  title = {{PLEIADES: Building Temporal Kernels with Orthogonal Polynomials}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=A3ezGit0uB},
}

@inproceedings{iclr2024_convolutional_33506,
  title = {{Convolutional Deep Kernel Machines}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19569},
}

@inproceedings{icml2025_an_48412,
  title = {{An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44205},
}

@inproceedings{icml2026_wbmm_51874,
  title = {{WBMM: Windowed Batch Matrix Multiplication for Efficient Large Receptive Field Convolution}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Qg9Jcy788i},
}

@inproceedings{icml2026_spatially_55386,
  title = {{Spatially-Adaptive Gradient Re-parameterization for 3D Large Kernel Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=yUvMzLLyfE},
}

@inproceedings{neurips2024_reparameterized_72200,
  title = {{Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95141},
}

@inproceedings{neurips2024_stochastic_73992,
  title = {{Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93525},
}

@inproceedings{icml2024_receptive_43979,
  title = {{Receptive Fields As Experts in Convolutional Neural Architectures}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34473},
}

@inproceedings{icml2024_is_44501,
  title = {{Is Kernel Prediction More Powerful than Gating in Convolutional Neural Networks?}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33951},
}

@inproceedings{icml2025_one_46341,
  title = {{One-dimensional Path Convolution}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46220},
}

@inproceedings{neurips2026_kvnn_89853,
  title = {{kVNN: Learnable Volterra Network Kernels}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154695},
}

@inproceedings{neurips2026_kerneldna_95115,
  title = {{KernelDNA: Cross-Layer Kernel Sharing via Decoupled Neural Adapters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153535},
}