% Key papers for Acquisition function design (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2016_bayesian_55596,
  title = {{Bayesian Optimization with Robust Bayesian Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7420},
}

@inproceedings{neurips2017_practical_56582,
  title = {{Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8973},
}

@inproceedings{icml2018_stagewise_37000,
  title = {{Stagewise Safe Bayesian Optimization with Gaussian Processes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2466},
}

@inproceedings{neurips2018_maximizing_57360,
  title = {{Maximizing acquisition functions for Bayesian optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11938},
}

@inproceedings{icml2017_high_36216,
  title = {{High Dimensional Bayesian Optimization with Elastic Gaussian Process}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/554},
}

@inproceedings{neurips2016_bayesian_55600,
  title = {{Bayesian optimization under mixed constraints  with a slack-variable augmented Lagrangian}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7261},
}

@inproceedings{neurips2023_unexpected_66638,
  title = {{Unexpected Improvements to Expected Improvement for Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72985},
}

@inproceedings{icml2017_preferential_36345,
  title = {{Preferential Bayesian Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/565},
}

@inproceedings{neurips2016_batched_55593,
  title = {{Batched Gaussian Process Bandit Optimization via Determinantal Point Processes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7162},
}

@inproceedings{neurips2017_lookahead_56457,
  title = {{Lookahead  Bayesian Optimization with Inequality Constraints}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8978},
}

@inproceedings{neurips2020_multi_60354,
  title = {{Multi-Fidelity Bayesian Optimization via Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17561},
}

@inproceedings{neurips2017_process_56597,
  title = {{Process-constrained batch Bayesian optimisation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9125},
}

@inproceedings{neurips2019_practical_58822,
  title = {{Practical Two-Step Lookahead Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14009},
}

@inproceedings{neurips2018_automating_56883,
  title = {{Automating Bayesian optimization with Bayesian optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11581},
}

@inproceedings{aaai2021_mercer_980,
  title = {{Mercer Features for Efficient Combinatorial Bayesian Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/07210-mercer-features-for-efficient-combinatorial-bayesian-optimization/},
}

@inproceedings{aaai2018_bayesian_102563,
  title = {{Bayesian Functional Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11830},
}

@inproceedings{icml2020_a_37880,
  title = {{A Quantile-based Approach for Hyperparameter Transfer Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6483},
}

@inproceedings{aaai2021_top_1517,
  title = {{Top-k Ranking Bayesian Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09135-top-k-ranking-bayesian-optimization/},
}

@inproceedings{icml2017_local_36274,
  title = {{Local Bayesian Optimization of Motor Skills}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/748},
}

@inproceedings{icml2020_knowing_38354,
  title = {{Knowing The What But Not The Where in Bayesian Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6137},
}

@inproceedings{iclr2024_a_34459,
  title = {{A Study of Bayesian Neural Network Surrogates for Bayesian Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18615},
}

@inproceedings{neurips2024_cost_71972,
  title = {{Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95339},
}

@inproceedings{neurips2024_transition_73143,
  title = {{Transition Constrained Bayesian Optimization via Markov Decision Processes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94288},
}

@inproceedings{aaai2024_stochastic_7419,
  title = {{Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29158},
}

@inproceedings{aaai2025_boids_8218,
  title = {{BOIDS: High-Dimensional Bayesian Optimization via Incumbent-Guided Direction Lines and Subspace Embeddings}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34165},
}

@inproceedings{aaai2025_regional_10499,
  title = {{Regional Expected Improvement for Efficient Trust Region Selection in High-Dimensional Bayesian Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34161},
}

@inproceedings{iclr2024_a_34301,
  title = {{A General Framework for User-Guided Bayesian Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18774},
}

@inproceedings{iclr2024_adversarial_34657,
  title = {{Adversarial Causal Bayesian Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18417},
}

@inproceedings{icml2024_in_44560,
  title = {{In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33892},
}

@inproceedings{icml2024_boundary_44990,
  title = {{Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33462},
}

@inproceedings{iclr2025_standard_83235,
  title = {{Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28574},
}

@inproceedings{aaai2025_coffeeboost_8445,
  title = {{CoffeeBoost: Gradient Boosting Native Conformal Inference for Bayesian Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33982},
}

@inproceedings{aaai2025_modeling_9980,
  title = {{Modeling All Response Surfaces in One for Conditional Search Spaces}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34016},
}

@inproceedings{icml2024_malibo_43388,
  title = {{MALIBO: Meta-learning for Likelihood-free Bayesian Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35064},
}

@inproceedings{icml2024_accelerating_43416,
  title = {{Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35036},
}

@inproceedings{icml2024_bayesian_45550,
  title = {{Bayesian Optimization of Function Networks with Partial Evaluations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32902},
}

@inproceedings{icml2025_funbo_47649,
  title = {{FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44948},
}

@inproceedings{neurips2024_inversion_72334,
  title = {{Inversion-based Latent Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95013},
}

@inproceedings{neurips2024_batched_74413,
  title = {{Batched Energy-Entropy acquisition for Bayesian Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93157},
}

@inproceedings{iclr2025_optimistic_84057,
  title = {{Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27768},
}