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

@inproceedings{iclr2017_categorical_28375,
  title = {{Categorical Reparameterization with Gumbel-Softmax}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=rkE3y85ee},
}

@inproceedings{iclr2017_the_28303,
  title = {{The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=S1jE5L5gl},
}

@inproceedings{iclr2019_analyzing_29147,
  title = {{Analyzing Inverse Problems with Invertible Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/1018},
}

@inproceedings{neurips2017_rebar_56606,
  title = {{REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9049},
}

@inproceedings{neurips2018_implicit_57223,
  title = {{Implicit Reparameterization Gradients}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11068},
}

@inproceedings{neurips2016_backprop_55590,
  title = {{Backprop KF: Learning Discriminative Deterministic State Estimators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7347},
}

@inproceedings{iclr2018_backpropagation_28651,
  title = {{Backpropagation through the Void: Optimizing control variates for black-box gradient estimation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/192},
}

@inproceedings{neurips2016_reward_55965,
  title = {{Reward Augmented Maximum Likelihood for Neural Structured Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6901},
}

@inproceedings{aaai2021_lren_848,
  title = {{LREN: Low-Rank Embedded Network for Sample-Free Hyperspectral Anomaly Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04139-lren-low-rank-embedded-network-for-sample-free-hyperspectral-anomaly-detection/},
}

@inproceedings{aaai2022_metanode_2412,
  title = {{MetaNODE: Prototype Optimization as a Neural ODE for Few-Shot Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/09014-metanode-prototype-optimization-as-a-neural-ode-for-few-shot-learning/},
}

@inproceedings{neurips2020_gradient_59957,
  title = {{Gradient Estimation with Stochastic Softmax Tricks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18503},
}

@inproceedings{iclr2019_arm_29017,
  title = {{ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/942},
}

@inproceedings{neurips2020_differentiable_59698,
  title = {{Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17306},
}

@inproceedings{aaai2022_sampling_2696,
  title = {{Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian Noise}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/09669-sampling-based-robust-control-of-autonomous-systems-with-non-gaussian-noise/},
}

@inproceedings{neurips2020_probabilistic_60620,
  title = {{Probabilistic Orientation Estimation with Matrix Fisher Distributions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18619},
}

@inproceedings{iclr2022_how_31121,
  title = {{How to deal with missing data in supervised deep learning?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/5973},
}

@inproceedings{neurips2022_dimes_64170,
  title = {{DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54442},
}

@inproceedings{iclr2020_estimating_29854,
  title = {{Estimating Gradients for Discrete Random Variables by Sampling without Replacement}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rklEj2EFvB},
}

@inproceedings{icml2019_arsm_37116,
  title = {{ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4166},
}

@inproceedings{neurips2020_disarm_59708,
  title = {{DisARM: An Antithetic Gradient Estimator for Binary Latent Variables}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18955},
}

@inproceedings{aaai2024_multiple_6724,
  title = {{Multiple Hypothesis Dropout: Estimating the Parameters of Multi-Modal Output Distributions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29358},
}

@inproceedings{iclr2024_retasa_34181,
  title = {{ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18894},
}

@inproceedings{icml2024_winner_44432,
  title = {{Winner-takes-all learners are geometry-aware conditional density estimators}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34020},
}

@inproceedings{icml2026_a_52134,
  title = {{A hitchhiker's guide to Poisson gradient estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=T4Ibp5vLpE},
}

@inproceedings{icml2026_categorical_54113,
  title = {{Categorical Reparameterization with Denoising Diffusion Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=lxKyBy8NDn},
}

@inproceedings{neurips2024_the_70261,
  title = {{The Star Geometry of Critic-Based Regularizer Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96828},
}

@inproceedings{neurips2024_great_70667,
  title = {{Great Minds Think Alike: The Universal Convergence Trend of Input Salience}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96455},
}

@inproceedings{neurips2024_meta_71176,
  title = {{Meta-Learning Universal Priors Using Non-Injective Change of Variables}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96052},
}

@inproceedings{neurips2025_the_75191,
  title = {{The Computational Advantage of Depth in Learning High-Dimensional Hierarchical Targets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=5JcDVsV8pf},
}

@inproceedings{neurips2026_density_89602,
  title = {{Density-Ratio Losses for Post-Hoc Learning to Defer}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154375},
}

@inproceedings{neurips2026_fringe_93781,
  title = {{FRInGe: Distribution-Space Integrated Gradients with Fisher–Rao Geometry}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149612},
}

@inproceedings{icml2024_remedi_43368,
  title = {{REMEDI: Corrective Transformations for Improved Neural Entropy Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35084},
}

@inproceedings{icml2025_gefa_47285,
  title = {{GEFA: A General Feature Attribution Framework Using Proxy Gradient Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45304},
}

@inproceedings{icml2026_latent_52449,
  title = {{Latent Space Robust Optimization of Neural Processes with Aligned Stratified Order-Statistic Loss Reduction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=W76xuQcrzS},
}

@inproceedings{iclr2025_quadim_82013,
  title = {{QuaDiM: A Conditional Diffusion Model For Quantum State Property Estimation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29772},
}

@inproceedings{iclr2025_sfess_83556,
  title = {{SFESS: Score Function Estimators for \$k\$-Subset Sampling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28261},
}

@inproceedings{iclr2026_continuous_89008,
  title = {{Continuous multinomial logistic regression for neural decoding}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=theeeNBSTG},
}

@inproceedings{cvpr2026_neural_99312,
  title = {{Neural Mixture Density Processes}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Ding_Neural_Mixture_Density_Processes_CVPR_2026_paper.html},
}