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

@inproceedings{cvpr2018_a_12796,
  title = {{A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Liang_A_Hybrid_l1-l0_CVPR_2018_paper.html},
}

@inproceedings{aaai2018_spine_105837,
  title = {{SPINE: SParse Interpretable Neural Embeddings}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11935},
}

@inproceedings{neurips2022_on_66450,
  title = {{On the Parameterization and Initialization of Diagonal State Space Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52909},
}

@inproceedings{cvpr2022_a_18216,
  title = {{A Structured Dictionary Perspective on Implicit Neural Representations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2024_improved_23764,
  title = {{Improved Implicit Neural Representation with Fourier Reparameterized Training}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29193},
}

@inproceedings{neurips2018_on_57454,
  title = {{On Controllable Sparse Alternatives to Softmax}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11621},
}

@inproceedings{aaai2024_modwavemlp_6658,
  title = {{ModWaveMLP: MLP-Based Mode Decomposition and Wavelet Denoising Model to Defeat Complex Structures in Traffic Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28753},
}

@inproceedings{cvpr2023_tinc_22298,
  title = {{TINC: Tree-Structured Implicit Neural Compression}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21604},
}

@inproceedings{cvpr2023_polynomial_21895,
  title = {{Polynomial Implicit Neural Representations for Large Diverse Datasets}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22016},
}

@inproceedings{neurips2020_implicit_60048,
  title = {{Implicit Rank-Minimizing Autoencoder}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16989},
}

@inproceedings{aaai2017_sparse_104396,
  title = {{Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10773},
}

@inproceedings{icml2016_why_36029,
  title = {{Why Regularized Auto-Encoders learn Sparse Representation?}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/arpita16.html},
}

@inproceedings{iclr2023_how_33085,
  title = {{How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11476},
}

@inproceedings{iclr2025_scaling_83779,
  title = {{Scaling and evaluating sparse autoencoders}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28040},
}

@inproceedings{iclr2023_the_32630,
  title = {{The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11756},
}

@inproceedings{aaai2022_fractional_2125,
  title = {{Fractional Adaptive Linear Units}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08988-fractional-adaptive-linear-units/},
}

@inproceedings{aaai2024_harnessing_6195,
  title = {{Harnessing the Power of SVD: An SVA Module for Enhanced Signal Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29606},
}

@inproceedings{cvpr2025_tuning_27955,
  title = {{Tuning the Frequencies: Robust Training for Sinusoidal Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35116},
}

@inproceedings{icml2022_an_40245,
  title = {{An Intriguing Property of Geophysics Inversion}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17775},
}

@inproceedings{aaai2024_dsd_5578,
  title = {{DSD²: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29393},
}

@inproceedings{iclr2025_towards_80558,
  title = {{Towards Principled Evaluations of Sparse Autoencoders for Interpretability and Control}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31206},
}

@inproceedings{aaai2024_bertground_5254,
  title = {{BERTground: A Transformer-Based Model of Background Spectra on the ISS-Based NICER Space Telescope}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30335},
}

@inproceedings{cvpr2025_sinr_27524,
  title = {{SINR: Sparsity Driven Compressed Implicit Neural Representations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34535},
}

@inproceedings{cvpr2025_understanding_27992,
  title = {{Understanding Multi-layered Transmission Matrices}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33082},
}

@inproceedings{icml2024_deeppolar_45094,
  title = {{DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33358},
}

@inproceedings{iclr2024_robustifying_33945,
  title = {{Robustifying State-space Models for Long Sequences via Approximate Diagonalization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19130},
}

@inproceedings{icml2024_compression_43294,
  title = {{Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35158},
}

@inproceedings{icml2024_relus_45559,
  title = {{ReLUs Are Sufficient for Learning Implicit Neural Representations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32893},
}

@inproceedings{icml2025_universal_47498,
  title = {{Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45097},
}

@inproceedings{neurips2024_towards_73547,
  title = {{Towards Croppable Implicit Neural Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93932},
}

@inproceedings{neurips2024_improving_74631,
  title = {{Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/92961},
}

@inproceedings{neurips2025_from_76655,
  title = {{From Flat to Hierarchical: Extracting Sparse Representations with Matching Pursuit}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Ll5miDx8KB},
}

@inproceedings{iclr2026_sparse_85468,
  title = {{Sparse Autoencoders Trained on the Same Data Learn Different Features}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=EjInprGpk9},
}

@inproceedings{cvpr2024_from_23516,
  title = {{From Activation to Initialization: Scaling Insights for Optimizing Neural Fields}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29808},
}