% Key papers for High-dimensional Bayesian optimization (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2017_multi_36292,
  title = {{Multi-fidelity Bayesian Optimisation with Continuous Approximations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/596},
}

@inproceedings{neurips2018_scalable_57602,
  title = {{Scalable Hyperparameter Transfer Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11660},
}

@inproceedings{neurips2019_learning_58524,
  title = {{Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14227},
}

@inproceedings{neurips2020_learning_60195,
  title = {{Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18958},
}

@inproceedings{icml2017_batched_36078,
  title = {{Batched High-dimensional Bayesian Optimization via Structural Kernel Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/739},
}

@inproceedings{icml2021_think_40028,
  title = {{Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8551},
}

@inproceedings{icml2020_bayesian_37967,
  title = {{Bayesian Optimisation over Multiple Continuous and Categorical Inputs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6248},
}

@inproceedings{neurips2019_offline_58703,
  title = {{Offline Contextual Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13613},
}

@inproceedings{aaai2021_evolution_547,
  title = {{Evolution Strategies for Approximate Solution of Bayesian Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/05531-evolution-strategies-for-approximate-solution-of-bayesian-games/},
}

@inproceedings{aaai2019_bayesian_100621,
  title = {{Bayesian Functional Optimisation with Shape Prior}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3977},
}

@inproceedings{aaai2022_fourier_2124,
  title = {{Fourier Representations for Black-Box Optimization over Categorical Variables}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/10156-fourier-representations-for-black-box-optimization-over-categorical-variables/},
}

@inproceedings{neurips2021_combining_62843,
  title = {{Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28389},
}

@inproceedings{neurips2022_tree_63660,
  title = {{Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53330},
}

@inproceedings{icml2021_bayesian_39084,
  title = {{Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/10675},
}

@inproceedings{icml2021_bayesian_39088,
  title = {{Bayesian Optimization over Hybrid Spaces}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9183},
}

@inproceedings{aaai2019_red_103231,
  title = {{Red-Black Heuristics for Planning Tasks with Conditional Effects}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4755},
}

@inproceedings{aaai2024_grey_6164,
  title = {{Grey-Box Bayesian Optimization for Sensor Placement in Assisted Living Environments}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30208},
}

@inproceedings{icml2020_projective_38649,
  title = {{Projective Preferential Bayesian Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6141},
}

@inproceedings{neurips2019_learning_58470,
  title = {{Learning Bayesian Networks with Low Rank Conditional Probability Tables}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13944},
}

@inproceedings{neurips2024_a_72157,
  title = {{A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97688},
}

@inproceedings{neurips2024_this_73585,
  title = {{This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93900},
}

@inproceedings{neurips2025_bayesqp_76082,
  title = {{BayeSQP: Bayesian Optimization through Sequential Quadratic Programming}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=FEugj28qhC},
}

@inproceedings{neurips2025_optimizing_76878,
  title = {{Optimizing the Unknown: Black Box Bayesian Optimization with Energy-Based Model and Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=NwLOIEi9vX},
}

@inproceedings{icml2026_few_54374,
  title = {{Few-Shot Design Optimization by Exploiting Auxiliary Information}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=oQKiPx8jlI},
}

@inproceedings{neurips2024_monte_72288,
  title = {{Monte Carlo Tree Search based Space Transfer for Black Box Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95057},
}

@inproceedings{icml2025_bark_46566,
  title = {{BARK: A Fully Bayesian Tree Kernel for Black-box Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46003},
}

@inproceedings{icml2025_posterior_46630,
  title = {{Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45940},
}

@inproceedings{iclr2025_gaussian_82027,
  title = {{Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29758},
}