% Key papers for Kernel two-sample testing (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2020_learning_38374,
  title = {{Learning Deep Kernels for Non-Parametric Two-Sample Tests}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5999},
}

@inproceedings{neurips2016_minimax_55871,
  title = {{Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7286},
}

@inproceedings{icml2017_an_36060,
  title = {{An Adaptive Test of Independence with Analytic Kernel Embeddings}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/469},
}

@inproceedings{aaai2019_linear_101530,
  title = {{Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4222},
}

@inproceedings{neurips2020_learning_60177,
  title = {{Learning Kernel Tests Without Data Splitting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16816},
}

@inproceedings{neurips2022_efficient_66050,
  title = {{Efficient Aggregated Kernel Tests using Incomplete \$U\$-statistics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54933},
}

@inproceedings{neurips2019_comparing_58011,
  title = {{Comparing distributions: \$ell\_1\$ geometry improves kernel two-sample testing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14612},
}

@inproceedings{neurips2018_early_57077,
  title = {{Early Stopping for Nonparametric Testing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11396},
}

@inproceedings{neurips2021_a_62007,
  title = {{A Kernel-based Test of Independence for Cluster-correlated Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28475},
}

@inproceedings{neurips2023_mmd_67690,
  title = {{MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72060},
}

@inproceedings{neurips2023_statistical_69565,
  title = {{Statistical Insights into HSIC in High Dimensions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70361},
}

@inproceedings{neurips2022_a_64851,
  title = {{A permutation-free kernel two-sample test}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53967},
}

@inproceedings{neurips2020_a_59290,
  title = {{A kernel test for quasi-independence}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17256},
}

@inproceedings{neurips2021_meta_61702,
  title = {{Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26743},
}

@inproceedings{aaai2019_a_101808,
  title = {{A Powerful Global Test Statistic for Functional Statistical Inference}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4523},
}

@inproceedings{icml2026_are_53230,
  title = {{Are Two Datasets Close Enough With Statistical Significance? A Kernel Distributional Closeness Testing Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=dWuxvV7ekd},
}

@inproceedings{icml2026_sequential_55097,
  title = {{Sequential Kernel-based Conditional Independence Testing via Adaptive Betting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=vUMdIyTs9c},
}

@inproceedings{neurips2022_ksd_64133,
  title = {{KSD Aggregated Goodness-of-fit Test}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54932},
}

@inproceedings{neurips2025_dual_75833,
  title = {{DUAL: Learning Diverse Kernels for Aggregated Two-sample and Independence Testing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=CVekdZDzLG},
}

@inproceedings{neurips2025_anchor_77030,
  title = {{Anchor-based Maximum Discrepancy for Relative Similarity Testing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=PkSDCXP6LP},
}

@inproceedings{neurips2025_practical_77157,
  title = {{Practical Kernel Selection for Kernel-based Conditional Independence Test}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=R1CximX3Cw},
}

@inproceedings{neurips2025_on_77436,
  title = {{On the Hardness of Conditional Independence Testing In Practice}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Tn1M71PDfF},
}

@inproceedings{neurips2025_kernel_78685,
  title = {{Kernel conditional tests from learning-theoretic bounds}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=hJKDwf32Xu},
}

@inproceedings{icml2026_adaptive_49666,
  title = {{Adaptive Multiscale Binary Expansion Tests for Independence}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=4YRxhbbvdH},
}

@inproceedings{icml2026_kernel_50400,
  title = {{Kernel-based Maximum-of-difference Test for Two-sample Comparison}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=By7jm2W8BY},
}

@inproceedings{icml2026_a_51901,
  title = {{A Studentized Spherical Harmonics–Based Nonparametric Two-Sample Test for Compositional and Directional Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=QsxpsAu7l1},
}

@inproceedings{neurips2026_minimax_89949,
  title = {{Minimax Optimal Kernel Two-sample Testing in Sub-quadratic Time}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149505},
}

@inproceedings{neurips2026_high_93006,
  title = {{High-Dimensional Conditional Independence Testing via Random Projection Aggregation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/148200},
}

@inproceedings{neurips2026_kernel_95520,
  title = {{Kernel Selection is Model Selection: A Unified Complexity-Penalised Approach for MMD Two-Sample Tests}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153658},
}