% Key papers for Bayesian decision-making under uncertainty (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2020_probabilistic_16065,
  title = {{Probabilistic Regression for Visual Tracking}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2020_multi_60356,
  title = {{Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18461},
}

@inproceedings{aaai2017_counting_104600,
  title = {{Counting-Based Reliability Estimation for Power-Transmission Grids}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11178},
}

@inproceedings{aaai2021_deep_392,
  title = {{Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/02628-deep-probabilistic-imaging-uncertainty-quantification-and-multi-modal-solution-characterization-for-computational-imaging/},
}

@inproceedings{cvpr2024_producing_24521,
  title = {{Producing and Leveraging Online Map Uncertainty in Trajectory Prediction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31399},
}

@inproceedings{aaai2019_probabilistic_103389,
  title = {{Probabilistic Model Checking of Robots Deployed in Extreme Environments}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4809},
}

@inproceedings{aaai2023_probabilities_4420,
  title = {{Probabilities Are Not Enough: Formal Controller Synthesis for Stochastic Dynamical Models with Epistemic Uncertainty}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26718},
}

@inproceedings{aaai2016_a_105351,
  title = {{A Proactive Sampling Approach to Project Scheduling under Uncertainty}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10404},
}

@inproceedings{icml2023_synthetic_41983,
  title = {{Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23943},
}

@inproceedings{aaai2023_evidential_3601,
  title = {{Evidential Conditional Neural Processes}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26125},
}

@inproceedings{aaai2025_dutytte_8837,
  title = {{DutyTTE: Deciphering Uncertainty in Origin-Destination Travel Time Estimation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33350},
}

@inproceedings{icml2020_uncertainty_38895,
  title = {{Uncertainty-Aware Lookahead Factor Models for Quantitative Investing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5869},
}

@inproceedings{neurips2020_bootstrapping_59481,
  title = {{Bootstrapping neural processes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17786},
}

@inproceedings{neurips2021_shifts_63239,
  title = {{Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=qM45LHaWM6E},
}

@inproceedings{aaai2021_dependency_416,
  title = {{Dependency Stochastic Boolean Satisfiability: A Logical Formalism for NEXPTIME Decision Problems with Uncertainty}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/03877-dependency-stochastic-boolean-satisfiability-a-logical-formalism-for-nexptime-decision-problems-with-uncertainty/},
}

@inproceedings{aaai2024_learning_6445,
  title = {{Learning Diffusions under Uncertainty}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30026},
}

@inproceedings{aaai2025_solving_10792,
  title = {{Solving Robust Markov Decision Processes: Generic, Reliable, Efficient}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34865},
}

@inproceedings{iclr2022_counterfactual_31670,
  title = {{Counterfactual Plans under Distributional Ambiguity}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6806},
}

@inproceedings{icml2020_selective_38741,
  title = {{Selective Dyna-Style Planning Under Limited Model Capacity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6672},
}

@inproceedings{neurips2024_hierarchical_72400,
  title = {{Hierarchical Uncertainty Exploration via Feedforward Posterior Trees}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94955},
}

@inproceedings{aaai2024_uncertainty_7675,
  title = {{Uncertainty Quantification for Data-Driven Change-Point Learning via Cross-Validation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29008},
}

@inproceedings{cvpr2025_rate_27379,
  title = {{Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33656},
}

@inproceedings{aaai2024_robust_7166,
  title = {{Robust Active Measuring under Model Uncertainty}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30122},
}

@inproceedings{cvpr2024_uncertainty_25115,
  title = {{Uncertainty Visualization via Low-Dimensional Posterior Projections}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31602},
}

@inproceedings{aaai2025_quantitative_10418,
  title = {{Quantitative Predictive Monitoring and Control for Safe Human-Machine Interaction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34817},
}

@inproceedings{aaai2025_statistical_10839,
  title = {{Statistical Methodologies for Decision-Making and Uncertainty Reduction in Machine Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35236},
}

@inproceedings{icml2024_a_44248,
  title = {{A Bayesian Approach to Online Planning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34204},
}

@inproceedings{icml2026_interventional_50403,
  title = {{Interventional Processes For Causal Uncertainty Quantification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=BzG0xtGjjr},
}

@inproceedings{icml2026_active_52821,
  title = {{Active Timepoint Selection for Learning Measure-Valued Trajectories}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ZLraoxBly2},
}

@inproceedings{icml2026_blips_52835,
  title = {{BLIPs: Bayesian Learned Interatomic Potentials}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ZSZW2diTs5},
}

@inproceedings{icml2026_disentangling_55088,
  title = {{Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=vNfbqRzash},
}

@inproceedings{neurips2025_unveiling_75558,
  title = {{Unveiling the Uncertainty in Embodied and Operational Carbon of Large AI Models through a Probabilistic Carbon Accounting Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=9QyNYxKeKr},
}

@inproceedings{neurips2025_prescribe_75621,
  title = {{PRESCRIBE: Predicting Single-Cell Responses with Bayesian Estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=A5O41ntKjk},
}

@inproceedings{neurips2025_robust_78368,
  title = {{Robust Sampling for Active Statistical Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=duVF6odtBO},
}

@inproceedings{neurips2025_scaling_79516,
  title = {{Scaling Epidemic Inference on Contact Networks: Theory and Algorithms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=qF5IrJfJDS},
}