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

@inproceedings{neurips2018_neural_57424,
  title = {{Neural Architecture Search with Bayesian Optimisation and Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11214},
}

@inproceedings{cvpr2021_a_16536,
  title = {{A Generalized Loss Function for Crowd Counting and Localization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{neurips2020_distribution_59724,
  title = {{Distribution Matching for Crowd Counting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18013},
}

@inproceedings{cvpr2020_semantic_16217,
  title = {{Semantic Correspondence as an Optimal Transport Problem}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2021_learning_918,
  title = {{Learning to Count via Unbalanced Optimal Transport}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/02319-learning-to-count-via-unbalanced-optimal-transport/},
}

@inproceedings{cvpr2021_fast_17009,
  title = {{Fast Sinkhorn Filters: Using Matrix Scaling for Non-Rigid Shape Correspondence With Functional Maps}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{icml2019_obtaining_37586,
  title = {{Obtaining Fairness using Optimal Transport Theory}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4010},
}

@inproceedings{neurips2019_hierarchical_58367,
  title = {{Hierarchical Optimal Transport for Document Representation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13372},
}

@inproceedings{neurips2019_differentiable_58128,
  title = {{Differentiable Ranking and Sorting using Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14545},
}

@inproceedings{aaai2020_a_101911,
  title = {{A General Approach to Fairness with Optimal Transport}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5771},
}

@inproceedings{icml2020_missing_38458,
  title = {{Missing Data Imputation using Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6455},
}

@inproceedings{neurips2020_cot_59498,
  title = {{COT-GAN: Generating Sequential Data via Causal Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17430},
}

@inproceedings{aaai2019_oversampling_101788,
  title = {{Oversampling for Imbalanced Data via Optimal Transport}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4503},
}

@inproceedings{icml2021_unbalanced_40068,
  title = {{Unbalanced minibatch Optimal Transport; applications to Domain Adaptation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8555},
}

@inproceedings{neurips2018_large_57266,
  title = {{Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11928},
}

@inproceedings{neurips2020_differentiable_59699,
  title = {{Differentiable Top-k with Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18028},
}

@inproceedings{aaai2019_guiding_101648,
  title = {{Guiding the One-to-One Mapping in CycleGAN via Optimal Transport}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4355},
}

@inproceedings{icml2020_adversarial_37921,
  title = {{Adversarial Risk via Optimal Transport and Optimal Couplings}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6263},
}

@inproceedings{cvpr2022_bending_18353,
  title = {{Bending Graphs: Hierarchical Shape Matching Using Gated Optimal Transport}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{neurips2019_discriminator_58148,
  title = {{Discriminator optimal transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13786},
}

@inproceedings{aaai2024_hierarchical_6205,
  title = {{Hierarchical Multi-Marginal Optimal Transport for Network Alignment}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29605},
}

@inproceedings{aaai2024_an_5186,
  title = {{An Optimal Transport View for Subspace Clustering and Spectral Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29563},
}

@inproceedings{iclr2024_adversarial_33714,
  title = {{Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19361},
}

@inproceedings{cvpr2025_optical_27098,
  title = {{OPTICAL: Leveraging Optimal Transport for Contribution Allocation in Dataset Distillation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32983},
}

@inproceedings{iclr2025_learning_82981,
  title = {{Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28822},
}

@inproceedings{neurips2024_automatic_74274,
  title = {{Automatic Outlier Rectification via Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93283},
}

@inproceedings{iclr2025_sava_80509,
  title = {{SAVA: Scalable Learning-Agnostic Data Valuation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31253},
}

@inproceedings{iclr2025_comparing_82744,
  title = {{Comparing noisy neural population dynamics using optimal transport distances}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29054},
}

@inproceedings{aaai2026_departures_106838,
  title = {{Departures: Distributional Transport for Single-Cell Perturbation Prediction with Neural Schrödinger Bridges}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39190},
}

@inproceedings{aaai2025_auditing_8180,
  title = {{Auditing and Enforcing Conditional Fairness via Optimal Transport}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33847},
}

@inproceedings{iclr2024_lcot_33598,
  title = {{LCOT: Linear Circular Optimal Transport}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19477},
}

@inproceedings{icml2024_generative_43928,
  title = {{Generative Conditional Distributions by Neural (Entropic) Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34524},
}

@inproceedings{icml2024_neural_44021,
  title = {{Neural Networks Learn Statistics of Increasing Complexity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34431},
}

@inproceedings{icml2025_joint_45865,
  title = {{Joint Metric Space Embedding by Unbalanced Optimal Transport with Gromov–Wasserstein Marginal Penalization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46678},
}

@inproceedings{icml2025_tarot_46656,
  title = {{TAROT: Targeted Data Selection via Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45916},
}

@inproceedings{icml2025_tightening_47398,
  title = {{Tightening Causal Bounds via Covariate-Aware Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45194},
}

@inproceedings{icml2026_inverse_49261,
  title = {{Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=0p617sK4Z4},
}

@inproceedings{icml2026_itspace_50366,
  title = {{ITSPACE: Monotone Gaussian Optimal Transport Updates}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=BdCjuNqZst},
}

@inproceedings{icml2026_optimal_50529,
  title = {{Optimal Transport Group Counterfactual Explanations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=DIWkLvYXuP},
}

@inproceedings{icml2026_avatar_52542,
  title = {{AvAtar: Learning to Align via Active Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=X0wQLbleXa},
}