% Key papers for Density and property estimation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_fast_12263,
  title = {{Fast Fourier Color Constancy}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2016_local_55855,
  title = {{Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7138},
}

@inproceedings{icml2016_mixture_35908,
  title = {{Mixture Proportion Estimation via Kernel Embeddings of Distributions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/ramaswamy16.html},
}

@inproceedings{icml2017_uniform_36442,
  title = {{Uniform Convergence Rates for Kernel Density Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/545},
}

@inproceedings{cvpr2018_an_12833,
  title = {{An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Yu_An_Efficient_and_CVPR_2018_paper.html},
}

@inproceedings{icml2016_linking_35893,
  title = {{Linking losses for density ratio and class-probability estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/menon16.html},
}

@inproceedings{icml2016_fast_35834,
  title = {{Fast Algorithms for Segmented Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/acharya16.html},
}

@inproceedings{neurips2016_decorrelated_55658,
  title = {{DECOrrelated feature space partitioning for distributed sparse regression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6997},
}

@inproceedings{neurips2017_learning_56430,
  title = {{Learning Populations of Parameters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9351},
}

@inproceedings{icml2017_density_36144,
  title = {{Density Level Set Estimation on Manifolds with DBSCAN}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/552},
}

@inproceedings{icml2019_uniform_37836,
  title = {{Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4108},
}

@inproceedings{icml2020_quantum_38664,
  title = {{Quantum Expectation-Maximization for Gaussian mixture models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6102},
}

@inproceedings{icml2016_generalized_35852,
  title = {{Generalized Direct Change Estimation in Ising Model Structure}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/fazayeli16.html},
}

@inproceedings{neurips2018_theoretical_57706,
  title = {{Theoretical guarantees for EM under misspecified Gaussian mixture models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11920},
}

@inproceedings{aaai2021_almost_115,
  title = {{Almost Linear Time Density Level Set Estimation via DBSCAN}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/07349-almost-linear-time-density-level-set-estimation-via-dbscan/},
}

@inproceedings{icml2020_acceleration_37899,
  title = {{Acceleration through spectral density estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5794},
}

@inproceedings{icml2022_robust_41112,
  title = {{Robust Kernel Density Estimation with Median-of-Means principle}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16259},
}

@inproceedings{icml2023_score_42051,
  title = {{Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23598},
}

@inproceedings{icml2023_diffusion_42184,
  title = {{Diffusion Models are Minimax Optimal Distribution Estimators}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23996},
}

@inproceedings{neurips2016_agnostic_55570,
  title = {{Agnostic Estimation for Misspecified Phase Retrieval Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7102},
}

@inproceedings{cvpr2025_image_26590,
  title = {{Image Reconstruction from Readout-Multiplexed Single-Photon Detector Arrays}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34628},
}

@inproceedings{icml2024_bagged_44036,
  title = {{Bagged Deep Image Prior for Recovering Images in the Presence of Speckle Noise}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34416},
}

@inproceedings{icml2024_minimax_45704,
  title = {{Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32748},
}

@inproceedings{neurips2024_instance_70975,
  title = {{Instance-Optimal Private Density Estimation in the Wasserstein Distance}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96229},
}

@inproceedings{neurips2024_nonparametric_71349,
  title = {{Nonparametric Evaluation of Noisy ICA Solutions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95900},
}

@inproceedings{icml2024_overcoming_44196,
  title = {{Overcoming Saturation in Density Ratio Estimation by Iterated Regularization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34256},
}

@inproceedings{icml2026_approximating_49871,
  title = {{Approximating f -Divergences with Rank Statistics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=6dI31vzkqT},
}

@inproceedings{icml2026_diffusion_51334,
  title = {{Diffusion Models Are Statistically Optimal for Learning Low-Dimensional Multi-Modal Distributions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=L5JTAPUdbQ},
}

@inproceedings{icml2026_transfer_51902,
  title = {{Transfer Learning in High-dimensional Ising Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=QuvgxpbVzf},
}

@inproceedings{icml2026_diffusion_55501,
  title = {{Diffusion Flow Matching: Dimension-Improved KL Bounds and Wasserstein Guarantees}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=zl3akehFBq},
}

@inproceedings{neurips2024_breaking_73092,
  title = {{Breaking the curse of dimensionality in structured density estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94337},
}

@inproceedings{neurips2025_assessing_75822,
  title = {{Assessing the quality of denoising diffusion models in Wasserstein distance: noisy score and optimal bounds}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=CI7ZQnZTKu},
}

@inproceedings{neurips2025_absorb_77629,
  title = {{Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=VsZzTSyk5p},
}

@inproceedings{neurips2025_sparse_78341,
  title = {{Sparse Polyak: an adaptive step size rule for high-dimensional M-estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=ddyJqXyCxE},
}

@inproceedings{iclr2026_learning_84637,
  title = {{Learning a distance measure from the information-estimation geometry of data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=4uTZobABec},
}

@inproceedings{iclr2026_complexity_84993,
  title = {{Complexity Analysis of Normalizing Constant Estimation: from Jarzynski Equality to Annealed Importance Sampling and beyond}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=96fJALwotm},
}

@inproceedings{iclr2026_special_86932,
  title = {{Special Unitary Parameterized Estimators of Rotation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=VaS6xcDrTb},
}

@inproceedings{neurips2026_nearest_89928,
  title = {{Nearest-Neighbor Radii under Dependent Sampling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150949},
}

@inproceedings{icml2026_mixtures_49958,
  title = {{Mixtures of geodesic factor analyzers on Riemannian homogeneous spaces}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=7bTdGPe3RG},
}

@inproceedings{icml2026_the_52759,
  title = {{The Accumulation of Score Estimation Error in Diffusion Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=YoGDpLRqN8},
}