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

@inproceedings{icml2017_sliced_36396,
  title = {{Sliced Wasserstein Kernel for Persistence Diagrams}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/524},
}

@inproceedings{cvpr2016_sliced_11870,
  title = {{Sliced Wasserstein Kernels for Probability Distributions}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2019_sliced_58989,
  title = {{Sliced Gromov-Wasserstein}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14385},
}

@inproceedings{icml2019_linear_37515,
  title = {{Linear-Complexity Data-Parallel Earth Mover’s Distance Approximations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3568},
}

@inproceedings{icml2020_scalable_38735,
  title = {{Scalable Nearest Neighbor Search for Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6078},
}

@inproceedings{iclr2021_distributional_30295,
  title = {{Distributional Sliced-Wasserstein and Applications to Generative Modeling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3072},
}

@inproceedings{aaai2016_flattening_105068,
  title = {{Flattening the Density Gradient for Eliminating Spatial Centrality to Reduce Hubness}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10240},
}

@inproceedings{iclr2018_learning_28608,
  title = {{Learning Wasserstein Embeddings}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/305},
}

@inproceedings{neurips2023_near_67877,
  title = {{Near-Linear Time Algorithm for the Chamfer Distance}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71889},
}

@inproceedings{neurips2020_projection_60627,
  title = {{Projection Robust Wasserstein Distance and Riemannian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16986},
}

@inproceedings{neurips2022_distributional_65884,
  title = {{Distributional Convergence of the Sliced Wasserstein Process}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54667},
}

@inproceedings{iclr2022_augmented_31585,
  title = {{Augmented Sliced Wasserstein Distances}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6818},
}

@inproceedings{neurips2021_fast_63168,
  title = {{Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27618},
}

@inproceedings{neurips2022_amortized_63795,
  title = {{Amortized Projection Optimization for Sliced Wasserstein Generative Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54653},
}

@inproceedings{neurips2022_revisiting_64788,
  title = {{Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54654},
}

@inproceedings{neurips2019_tree_59119,
  title = {{Tree-Sliced Variants of Wasserstein Distances}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14189},
}

@inproceedings{iclr2023_hierarchical_32234,
  title = {{Hierarchical Sliced Wasserstein Distance}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11704},
}

@inproceedings{icml2022_unsupervised_41322,
  title = {{Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/18307},
}

@inproceedings{iclr2023_spherical_33044,
  title = {{Spherical Sliced-Wasserstein}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11997},
}

@inproceedings{icml2023_shedding_42569,
  title = {{Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24959},
}

@inproceedings{aaai2026_a_107317,
  title = {{A Novel Sliced Fused Gromov-Wasserstein Distance}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39669},
}

@inproceedings{icml2024_stereographic_45669,
  title = {{Stereographic Spherical Sliced Wasserstein Distances}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32783},
}

@inproceedings{icml2025_statistical_46242,
  title = {{Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46318},
}

@inproceedings{icml2025_towards_47170,
  title = {{Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45417},
}

@inproceedings{icml2025_tree_47394,
  title = {{Tree-Sliced Wasserstein Distance: A Geometric Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45198},
}

@inproceedings{icml2025_tree_47399,
  title = {{Tree-Sliced Wasserstein Distance with Nonlinear Projection}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45193},
}

@inproceedings{icml2025_lightspeed_48721,
  title = {{Lightspeed Geometric Dataset Distance via Sliced Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43901},
}

@inproceedings{icml2026_streaming_53700,
  title = {{Streaming Sliced Optimal Transport}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=hrypB1oTC3},
}

@inproceedings{neurips2025_tree_75078,
  title = {{Tree-Sliced Entropy Partial Transport}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=41ZbysfW4h},
}

@inproceedings{neurips2025_differentiable_78687,
  title = {{Differentiable Generalized Sliced Wasserstein Plans}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=hKKbtN4cp9},
}

@inproceedings{iclr2025_fast_81413,
  title = {{Fast unsupervised ground metric learning with tree-Wasserstein distance}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30359},
}

@inproceedings{iclr2025_spherical_81429,
  title = {{Spherical Tree-Sliced Wasserstein Distance}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30344},
}

@inproceedings{iclr2025_towards_81907,
  title = {{Towards Marginal Fairness Sliced Wasserstein Barycenter}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29877},
}

@inproceedings{iclr2025_distance_81980,
  title = {{Distance-Based Tree-Sliced Wasserstein Distance}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29805},
}

@inproceedings{iclr2025_linear_82938,
  title = {{Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28865},
}

@inproceedings{iclr2025_partial_83679,
  title = {{Partial Gromov-Wasserstein Metric}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28140},
}

@inproceedings{iclr2026_tree_85701,
  title = {{Tree-sliced Sobolev IPM}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=HHNQSXaLkF},
}

@inproceedings{iclr2026_mixed_87660,
  title = {{Mixed-Curvature Tree-Sliced Wasserstein Distance}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=e439wJl5sT},
}

@inproceedings{iclr2026_revisiting_88196,
  title = {{Revisiting Tree-Sliced Wasserstein Distance Through the Lens of the Fermat–Weber Problem}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=kDqG03v05B},
}

@inproceedings{neurips2026_sliced_95246,
  title = {{Sliced Inner Product Gromov–Wasserstein Distances}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150301},
}