% Key papers for Monte Carlo tree search (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2017_count_36121,
  title = {{Count-Based Exploration with Neural Density Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/839},
}

@inproceedings{icml2018_learning_36810,
  title = {{Learning to Branch}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2244},
}

@inproceedings{aaai2017_an_106041,
  title = {{An Analysis of Monte Carlo Tree Search}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11028},
}

@inproceedings{neurips2018_monte_57392,
  title = {{Monte-Carlo Tree Search for Constrained POMDPs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11760},
}

@inproceedings{aaai2020_monte_103264,
  title = {{Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6546},
}

@inproceedings{neurips2019_depth_58120,
  title = {{Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13814},
}

@inproceedings{iclr2022_efficient_31657,
  title = {{Efficient Active Search for Combinatorial Optimization Problems}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6761},
}

@inproceedings{icml2018_learning_36817,
  title = {{Learning to search with MCTSnets}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2233},
}

@inproceedings{neurips2017_monte_56483,
  title = {{Monte-Carlo Tree Search by Best Arm Identification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9266},
}

@inproceedings{aaai2020_a_101061,
  title = {{A Learning Based Branch and Bound for Maximum Common Subgraph Related Problems}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5619},
}

@inproceedings{aaai2016_nested_104814,
  title = {{Nested Monte Carlo Search for Two-Player Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10073},
}

@inproceedings{aaai2018_memory_101108,
  title = {{Memory-Augmented Monte Carlo Tree Search}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11531},
}

@inproceedings{neurips2018_single_57627,
  title = {{Single-Agent Policy Tree Search With Guarantees}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11324},
}

@inproceedings{aaai2020_monte_102023,
  title = {{Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5885},
}

@inproceedings{aaai2016_learning_105360,
  title = {{Learning Bayesian Networks with Bounded Tree-width via Guided Search}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10418},
}

@inproceedings{aaai2021_anytime_138,
  title = {{Anytime Heuristic and Monte Carlo Methods for Large-Scale Simultaneous Coalition Structure Generation and Assignment}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/11317-anytime-heuristic-and-monte-carlo-methods-for-large-scale-simultaneous-coalition-structure-generation-and-assignment/},
}

@inproceedings{iclr2021_practical_30019,
  title = {{Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2528},
}

@inproceedings{icml2020_learning_38384,
  title = {{Learning Optimal Tree Models under Beam Search}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6164},
}

@inproceedings{neurips2018_efficient_57087,
  title = {{Efficient Projection onto the Perfect Phylogeny Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11407},
}

@inproceedings{aaai2017_beyond_105707,
  title = {{Beyond Monte Carlo Tree Search: Playing Go with Deep Alternative Neural Network and Long-Term Evaluation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10749},
}

@inproceedings{aaai2025_search_10701,
  title = {{Search Strategy Generation for Branch and Bound Using Genetic Programming}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33229},
}

@inproceedings{aaai2024_sample_7254,
  title = {{Sample-and-Bound for Non-convex Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30074},
}

@inproceedings{neurips2024_speculative_73270,
  title = {{Speculative Monte-Carlo Tree Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94170},
}

@inproceedings{neurips2024_seea_73744,
  title = {{SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93757},
}

@inproceedings{aaai2025_a_7910,
  title = {{A Multiagent Path Search Algorithm for Large-Scale Coalition Structure Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34498},
}

@inproceedings{aaai2025_threshold_10996,
  title = {{Threshold UCT: Cost-Constrained Monte Carlo Tree Search with Pareto Curves}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34858},
}

@inproceedings{icml2024_position_44852,
  title = {{Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33600},
}

@inproceedings{icml2025_branches_48417,
  title = {{Branches: Efficiently Seeking Optimal Sparse Decision Trees via AO*}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44200},
}

@inproceedings{neurips2025_improving_77704,
  title = {{Improving Monte Carlo Tree Search for Symbolic Regression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Wic0OgYsgy},
}

@inproceedings{neurips2025_keea_78117,
  title = {{KeeA*: Epistemic Exploratory A* Search via Knowledge Calibration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=b8j0Gbg4N3},
}

@inproceedings{iclr2025_strength_81283,
  title = {{Strength Estimation and Human-Like Strength Adjustment in Games}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30488},
}

@inproceedings{iclr2026_beyond_85677,
  title = {{Beyond the Heatmap: A Rigorous Evaluation of Component Impact in MCTS-Based TSP Solvers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=H6PLJnnK6e},
}

@inproceedings{neurips2026_an_92736,
  title = {{An Efficient Algorithm for Thresholding Monte Carlo Tree Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153387},
}

@inproceedings{neurips2026_graph_93030,
  title = {{Graph-Based Stochastic-Power-UCT: Monte-Carlo Graph Search with Power Mean Estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154641},
}

@inproceedings{aaai2026_nested_108680,
  title = {{Nested Depth Search}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/41032},
}

@inproceedings{icml2026_apex_49794,
  title = {{APEX: Approximate-but-exhaustive search for ultra-large combinatorial synthesis libraries}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=5lIJrDCQll},
}

@inproceedings{icml2026_recursive_54424,
  title = {{Recursive Monte-Carlo Tree Search}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=oo9523XUWI},
}

@inproceedings{iclr2025_epistemic_82259,
  title = {{Epistemic Monte Carlo Tree Search}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29531},
}

@inproceedings{iclr2025_carts_82379,
  title = {{CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29413},
}

@inproceedings{iclr2025_grammar_84085,
  title = {{Grammar Reinforcement Learning: path and cycle counting in graphs with a Context-Free Grammar and Transformer approach}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27743},
}