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

@inproceedings{neurips2016_mapping_55861,
  title = {{Mapping Estimation for Discrete Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7170},
}

@inproceedings{neurips2020_entropic_59790,
  title = {{Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17334},
}

@inproceedings{neurips2019_hierarchical_58368,
  title = {{Hierarchical Optimal Transport for Multimodal Distribution Alignment}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14283},
}

@inproceedings{neurips2020_partial_60571,
  title = {{Partial Optimal Tranport with applications on Positive-Unlabeled Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18457},
}

@inproceedings{neurips2021_rates_62840,
  title = {{Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26819},
}

@inproceedings{icml2021_outlier_39758,
  title = {{Outlier-Robust Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9841},
}

@inproceedings{neurips2022_supervised_66173,
  title = {{Supervised Training of Conditional Monge Maps}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53123},
}

@inproceedings{neurips2019_a_57811,
  title = {{A Graph Theoretic Additive Approximation of Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14312},
}

@inproceedings{icml2020_a_37884,
  title = {{A Swiss Army Knife for Minimax Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6474},
}

@inproceedings{icml2021_optimal_39749,
  title = {{Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9843},
}

@inproceedings{neurips2021_do_61629,
  title = {{Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28673},
}

@inproceedings{neurips2020_statistical_60868,
  title = {{Statistical Optimal Transport posed as Learning Kernel Embedding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18356},
}

@inproceedings{cvpr2023_sliced_22221,
  title = {{Sliced Optimal Partial Transport}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21043},
}

@inproceedings{icml2022_linear_40790,
  title = {{Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/18353},
}

@inproceedings{icml2019_on_37594,
  title = {{On Scalable and Efficient Computation of Large Scale Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3918},
}

@inproceedings{icml2022_debiaser_40412,
  title = {{Debiaser Beware: Pitfalls of Centering Regularized Transport Maps}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16639},
}

@inproceedings{neurips2022_low_63875,
  title = {{Low-rank Optimal Transport: Approximation, Statistics and Debiasing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54640},
}

@inproceedings{aaai2022_optimal_2518,
  title = {{Optimal Tensor Transport}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07124-optimal-tensor-transport/},
}

@inproceedings{aaai2024_double_5748,
  title = {{Double-Bounded Optimal Transport for Advanced Clustering and Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29419},
}

@inproceedings{iclr2023_neural_32892,
  title = {{Neural Optimal Transport}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11993},
}

@inproceedings{iclr2024_neural_34926,
  title = {{Neural Optimal Transport with General Cost Functionals}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18148},
}

@inproceedings{aaai2024_learning_6490,
  title = {{Learning Ultrametric Trees for Optimal Transport Regression}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30052},
}

@inproceedings{neurips2024_a_72639,
  title = {{A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94742},
}

@inproceedings{neurips2024_low_73369,
  title = {{Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94081},
}

@inproceedings{aaai2024_a_5049,
  title = {{A Novel Skip Orthogonal List for Dynamic Optimal Transport Problem}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30073},
}

@inproceedings{iclr2024_energy_34800,
  title = {{Energy-guided Entropic Neural Optimal Transport}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18274},
}

@inproceedings{iclr2024_sparsistency_35594,
  title = {{Sparsistency for inverse optimal transport}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17479},
}

@inproceedings{icml2024_generalized_43241,
  title = {{Generalized Sobolev Transport for Probability Measures on a Graph}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35211},
}

@inproceedings{icml2024_quantum_43670,
  title = {{Quantum Theory and Application of Contextual Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34782},
}

@inproceedings{icml2024_wasserstein_44465,
  title = {{Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33987},
}

@inproceedings{icml2024_estimating_45798,
  title = {{Estimating Barycenters of Distributions with Neural Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32654},
}

@inproceedings{icml2025_overcoming_45880,
  title = {{Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plan}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46663},
}

@inproceedings{icml2025_hierarchical_46604,
  title = {{Hierarchical Refinement: Optimal Transport to Infinity and Beyond}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45965},
}

@inproceedings{icml2025_on_48564,
  title = {{On the Private Estimation of Smooth Transport Maps}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44057},
}

@inproceedings{icml2026_variational_50565,
  title = {{Variational Entropic Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=DgRd1uu8dj},
}

@inproceedings{icml2026_loss_51229,
  title = {{Loss-Aware Distributionally Robust Optimization via Trainable Optimal Transport Ambiguity Sets}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=K1EPPO9t2c},
}

@inproceedings{icml2026_riemannian_53381,
  title = {{Riemannian Neural Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ez4oLq7PR3},
}

@inproceedings{icml2026_transport_53521,
  title = {{Transport Clustering: Solving Low-Rank Optimal Transport via Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=gGnfUcXMe8},
}

@inproceedings{icml2026_partial_54697,
  title = {{Partial Identification under High-Dimensional Potential Outcomes and Confounders via Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=raKcsJbVDY},
}