% Key papers for Nonparametric and PAC-Bayes Bayesian learning (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{iclr2023_tabpfn_32884,
  title = {{TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/12113},
}

@inproceedings{cvpr2019_bayesian_13888,
  title = {{Bayesian Hierarchical Dynamic Model for Human Action Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2023_robust_22076,
  title = {{Robust Outlier Rejection for 3D Registration With Variational Bayes}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21543},
}

@inproceedings{cvpr2022_bayesian_18351,
  title = {{Bayesian Invariant Risk Minimization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2021_marta_952,
  title = {{MARTA: Leveraging Human Rationales for Explainable Text Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/05868-marta-leveraging-human-rationales-for-explainable-text-classification/},
}

@inproceedings{aaai2018_an_101244,
  title = {{An Interpretable Joint Graphical Model for Fact-Checking From Crowds}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11487},
}

@inproceedings{neurips2016_learning_55829,
  title = {{Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7113},
}

@inproceedings{neurips2018_explaining_57112,
  title = {{Explaining Deep Learning Models -- A Bayesian Non-parametric Approach}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11445},
}

@inproceedings{neurips2018_nonparametric_57447,
  title = {{Nonparametric learning from Bayesian models with randomized objective functions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11219},
}

@inproceedings{neurips2020_learning_60240,
  title = {{Learning under Model Misspecification: Applications to Variational and Ensemble methods}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17584},
}

@inproceedings{aaai2019_automatic_101839,
  title = {{Automatic Bayesian Density Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4977},
}

@inproceedings{neurips2020_can_59507,
  title = {{Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18319},
}

@inproceedings{icml2016_estimating_35819,
  title = {{Estimating Accuracy from Unlabeled Data: A Bayesian Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/platanios16.html},
}

@inproceedings{cvpr2017_personalizing_12530,
  title = {{Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{icml2019_scalable_37723,
  title = {{Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4150},
}

@inproceedings{neurips2016_learning_55813,
  title = {{Learning Bayesian networks with ancestral constraints}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7272},
}

@inproceedings{aaai2019_bayesian_101773,
  title = {{Bayesian Deep Collaborative Matrix Factorization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4488},
}

@inproceedings{neurips2019_icebreaker_58385,
  title = {{Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14391},
}

@inproceedings{icml2017_bayesian_36079,
  title = {{Bayesian Boolean Matrix Factorisation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/716},
}

@inproceedings{neurips2018_generalizing_57166,
  title = {{Generalizing Tree Probability Estimation via Bayesian Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11160},
}

@inproceedings{aaai2024_bayesian_5273,
  title = {{Bayesian Inference with Complex Knowledge Graph Evidence}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30040},
}

@inproceedings{iclr2025_scalable_82940,
  title = {{Scalable Bayesian Learning with posteriors}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28863},
}

@inproceedings{icml2024_leveraging_43552,
  title = {{Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34900},
}

@inproceedings{icml2025_bayesian_48818,
  title = {{Bayesian Inference for Correlated Human Experts and Classifiers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43804},
}

@inproceedings{icml2025_latent_48932,
  title = {{Latent Variable Estimation in Bayesian Black-Litterman Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43691},
}

@inproceedings{icml2026_demystifying_50238,
  title = {{Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ANVg7NnupP},
}

@inproceedings{icml2026_optimal_51191,
  title = {{Optimal Bayesian Stopping for Efficient Inference of Consistent LLM Answers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=JXN3npSRRD},
}

@inproceedings{icml2026_fire_51226,
  title = {{FIRE: Multi-Fidelity Regression with Distribution-Conditioned In-Context Learning Using Tabular Foundation Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=JxbxHB5d9v},
}

@inproceedings{icml2026_efficient_51570,
  title = {{Efficient Bayesian Inference from Noisy Pairwise Comparisons}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=NinueNAODD},
}

@inproceedings{icml2026_accuracy_52089,
  title = {{Accuracy and Normalized Accuracy under Length Bias: Analysis, Guidelines, and a Bayesian Alternative}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=SbSFZ9N6DN},
}

@inproceedings{icml2026_de_52263,
  title = {{De-Linearizing Agent Traces: Bayesian Inference of Latent Partial Orders for Efficient Execution}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=UAXQW194WT},
}

@inproceedings{icml2026_adaptive_52702,
  title = {{Adaptive Querying with AI Persona Priors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=YJhBBARWHv},
}

@inproceedings{icml2026_anchor_54315,
  title = {{ANCHOR: Abductive Network Construction with Hierarchical Orchestration for Reliable Probability Inference in Large Language Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=no1Tgzkw0x},
}

@inproceedings{icml2026_mira_54696,
  title = {{MIRA: A Score for Conditional Distribution Accuracy and Model Comparison}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ra2t1V4nml},
}

@inproceedings{icml2026_joint_55081,
  title = {{Joint Model and Data Sparsification via the Marginal Likelihood}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=vMcu1h3fOV},
}

@inproceedings{icml2026_doubly_55270,
  title = {{Doubly Outlier-Robust Online Infinite Hidden Markov Model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=xAZHb0LUW1},
}

@inproceedings{icml2026_bayesian_55444,
  title = {{Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=z3rQmLk4Io},
}

@inproceedings{neurips2024_a_71093,
  title = {{A Metalearned Neural Circuit for Nonparametric Bayesian Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96121},
}

@inproceedings{neurips2024_recursive_71998,
  title = {{Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95315},
}

@inproceedings{neurips2024_probabilistic_73071,
  title = {{Probabilistic size-and-shape functional mixed models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94356},
}