% Key papers for Metric and ordinal embedding (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2018_representation_36959,
  title = {{Representation Tradeoffs for Hyperbolic Embeddings}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2289},
}

@inproceedings{icml2019_tensorfuzz_37789,
  title = {{TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4139},
}

@inproceedings{neurips2018_on_57467,
  title = {{On the Dimensionality of Word Embedding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11110},
}

@inproceedings{icml2019_rethinking_37698,
  title = {{Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3643},
}

@inproceedings{neurips2016_finite_55737,
  title = {{Finite Sample Prediction and Recovery Bounds for Ordinal Embedding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7323},
}

@inproceedings{icml2017_joint_36236,
  title = {{Joint Dimensionality Reduction and Metric Learning: A Geometric Take}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/561},
}

@inproceedings{cvpr2018_fast_13100,
  title = {{Fast Spectral Ranking for Similarity Search}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Iscen_Fast_Spectral_Ranking_CVPR_2018_paper.html},
}

@inproceedings{aaai2017_classification_104422,
  title = {{Classification with Minimax Distance Measures}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10799},
}

@inproceedings{neurips2016_nearly_55891,
  title = {{Nearly Isometric Embedding by Relaxation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6890},
}

@inproceedings{neurips2019_curvilinear_58073,
  title = {{Curvilinear Distance Metric Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13579},
}

@inproceedings{neurips2019_numerically_58696,
  title = {{Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14499},
}

@inproceedings{aaai2019_robust_101654,
  title = {{Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4361},
}

@inproceedings{icml2024_the_44502,
  title = {{The Linear Representation Hypothesis and the Geometry of Large Language Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33950},
}

@inproceedings{cvpr2016_spatially_11884,
  title = {{Spatially Binned ROC: A Comprehensive Saliency Metric}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{icml2019_learning_37478,
  title = {{Learning Distance for Sequences by Learning a Ground Metric}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3624},
}

@inproceedings{cvpr2020_revisiting_16130,
  title = {{Revisiting Saliency Metrics: Farthest-Neighbor Area Under Curve}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{icml2018_a_36475,
  title = {{A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2118},
}

@inproceedings{icml2019_scaling_37726,
  title = {{Scaling Up Ordinal Embedding: A Landmark Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4058},
}

@inproceedings{iclr2020_an_29446,
  title = {{An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HJeiDpVFPr},
}

@inproceedings{cvpr2025_finsler_26268,
  title = {{Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34971},
}

@inproceedings{aaai2024_implications_6279,
  title = {{Implications of Distance over Redistricting Maps: Central and Outlier Maps}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28825},
}

@inproceedings{aaai2024_levenshtein_6520,
  title = {{Levenshtein Distance Embedding with Poisson Regression for DNA Storage}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29509},
}

@inproceedings{aaai2024_multipartite_6723,
  title = {{Multipartite Entity Resolution: Motivating a K-Tuple Perspective (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30417},
}

@inproceedings{icml2024_dynamic_45516,
  title = {{Dynamic Facility Location in High Dimensional Euclidean Spaces}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32936},
}

@inproceedings{icml2025_fast_48318,
  title = {{Fast, Accurate Manifold Denoising by Tunneling Riemannian Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44296},
}

@inproceedings{icml2026_magnitude_50200,
  title = {{Magnitude Distance: A Geometric Measure of Dataset Similarity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=9ylPoHEKed},
}

@inproceedings{neurips2024_euclidean_71287,
  title = {{Euclidean distance compression via deep random features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95959},
}

@inproceedings{neurips2025_fully_77296,
  title = {{Fully Dynamic Algorithms for Chamfer Distance}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=SPLtr5UThn},
}

@inproceedings{iclr2026_lore_86518,
  title = {{LORE: Jointly Learning The Intrinsic Dimensionality and Relative Similarity Structure from Ordinal Data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=QmgEUx2Cd7},
}

@inproceedings{neurips2026_on_90091,
  title = {{On Generation in Metric Spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151982},
}

@inproceedings{aaai2026_order_106189,
  title = {{Order-Preserving Dimension Reduction for Multimodal Semantic Embedding}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38496},
}

@inproceedings{aaai2026_geopth_107601,
  title = {{GeoPTH: A Lightweight Approach to Category-Based Trajectory Retrieval via Geometric Prototype Trajectory Hashing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39953},
}

@inproceedings{icml2025_fully_48191,
  title = {{Fully Dynamic Embedding into \$ell\_p\$ Spaces}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44420},
}

@inproceedings{icml2026_relevance_49235,
  title = {{Relevance-Based Embeddings: Lightweight Candidate Retrieval via Heavy-Ranker Calls}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=0RNjyGzTSJ},
}

@inproceedings{neurips2024_persistent_70945,
  title = {{Persistent Homology for High-dimensional Data Based on Spectral Methods}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96258},
}