% Key papers for Sinkhorn and entropic OT algorithms (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_near_56504,
  title = {{Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8985},
}

@inproceedings{icml2019_on_37591,
  title = {{On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3800},
}

@inproceedings{neurips2019_statistical_59018,
  title = {{Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14523},
}

@inproceedings{aaai2017_tsallis_104477,
  title = {{Tsallis Regularized Optimal Transport and Ecological Inference}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10854},
}

@inproceedings{icml2020_on_38542,
  title = {{On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6163},
}

@inproceedings{neurips2019_screening_58955,
  title = {{Screening Sinkhorn Algorithm for Regularized Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14183},
}

@inproceedings{icml2020_debiased_38079,
  title = {{Debiased Sinkhorn barycenters}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6012},
}

@inproceedings{neurips2020_linear_60255,
  title = {{Linear Time Sinkhorn Divergences using Positive Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18710},
}

@inproceedings{cvpr2023_re_21985,
  title = {{Re-Basin via Implicit Sinkhorn Differentiation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21028},
}

@inproceedings{cvpr2021_hilbert_17123,
  title = {{Hilbert Sinkhorn Divergence for Optimal Transport}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{icml2020_regularized_38685,
  title = {{Regularized Optimal Transport is Ground Cost Adversarial}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6497},
}

@inproceedings{neurips2020_minmax_60314,
  title = {{MinMax Methods for Optimal Transport and Beyond: Regularization, Approximation and Numerics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18576},
}

@inproceedings{aaai2019_on_101038,
  title = {{On the Optimal Efficiency of Cost-Algebraic A*}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4067},
}

@inproceedings{neurips2019_a_57799,
  title = {{A Direct tildeO(1/epsilon) Iteration Parallel Algorithm for Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14126},
}

@inproceedings{neurips2021_unbalanced_62086,
  title = {{Unbalanced Optimal Transport through Non-negative Penalized Linear Regression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28293},
}

@inproceedings{neurips2021_on_63522,
  title = {{On Robust Optimal Transport: Computational Complexity and Barycenter Computation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27753},
}

@inproceedings{icml2021_scalable_39925,
  title = {{Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8777},
}

@inproceedings{icml2022_exact_40519,
  title = {{Exact Optimal Accelerated Complexity for Fixed-Point Iterations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17039},
}

@inproceedings{aaai2024_optimal_6868,
  title = {{Optimal Transport with Cyclic Symmetry}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29444},
}

@inproceedings{neurips2023_a_66695,
  title = {{A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72932},
}

@inproceedings{aaai2024_optimal_6869,
  title = {{Optimal Transport with Tempered Exponential Measures}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28957},
}

@inproceedings{iclr2024_accelerating_34197,
  title = {{Accelerating Sinkhorn algorithm with sparse Newton iterations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18878},
}

@inproceedings{neurips2024_bisimulation_71066,
  title = {{Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96145},
}

@inproceedings{iclr2024_swap_34207,
  title = {{SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18868},
}

@inproceedings{icml2024_submodular_44824,
  title = {{Submodular framework for structured-sparse optimal transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33628},
}

@inproceedings{icml2025_optimal_47123,
  title = {{Optimal Transport Barycenter via Nonconvex-Concave Minimax Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45464},
}

@inproceedings{icml2026_uotip_49981,
  title = {{UOTIP: Unbalanced Optimal Transport Map for Unpaired Inverse Problems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=7sIDvIywHQ},
}

@inproceedings{icml2026_optimal_50497,
  title = {{Optimal and Scalable MAPF via Multi-Marginal Optimal Transport and Schrödinger Bridges}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Cxdj2GYZ4c},
}

@inproceedings{icml2026_second_51406,
  title = {{Second-Order Smooth Planning with Optimal-Transport Bellman Smoothing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=LrNH0O3s45},
}

@inproceedings{icml2026_curegot_53453,
  title = {{cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=fgIg1oOMwk},
}

@inproceedings{icml2026_optimal_54902,
  title = {{Optimal Transport under Group Fairness Constraints}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=tibRKqUHcv},
}

@inproceedings{neurips2024_safe_71892,
  title = {{Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95411},
}

@inproceedings{neurips2025_variational_76386,
  title = {{Variational Regularized Unbalanced Optimal Transport: Single Network, Least Action}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Iguyg0LULD},
}

@inproceedings{neurips2025_unbalanced_77528,
  title = {{Unbalanced Optimal Total Variation Transport: A Theoretical Approach to Spatial Resource Allocation Problems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=UuhoYEaUhT},
}

@inproceedings{neurips2025_efficient_78820,
  title = {{Efficient Algorithms for Robust and Partial Semi-Discrete Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=iehVIoSDzu},
}

@inproceedings{neurips2025_solving_79690,
  title = {{Solving Discrete (Semi) Unbalanced Optimal Transport with Equivalent Transformation Mechanism and KKT-Multiplier Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=rzjWktciDM},
}

@inproceedings{iclr2025_a_82990,
  title = {{A Truncated Newton Method for Optimal Transport}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28814},
}

@inproceedings{iclr2025_one_83265,
  title = {{One for all and all for one: Efficient computation of partial Wasserstein distances on the line}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28547},
}

@inproceedings{neurips2026_minimax_89754,
  title = {{Minimax Optimal Estimation of Transport-Growth Pairs in Unbalanced Optimal Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152805},
}