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

@inproceedings{icml2018_improved_36746,
  title = {{Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2353},
}

@inproceedings{icml2018_thompson_37047,
  title = {{Thompson Sampling for Combinatorial Semi-Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2120},
}

@inproceedings{neurips2016_double_55689,
  title = {{Double Thompson Sampling for Dueling Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7336},
}

@inproceedings{iclr2021_neural_30698,
  title = {{Neural Thompson Sampling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2714},
}

@inproceedings{neurips2018_an_56864,
  title = {{An Information-Theoretic Analysis for Thompson Sampling with Many Actions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11412},
}

@inproceedings{neurips2019_thompson_59087,
  title = {{Thompson Sampling for Multinomial Logit Contextual Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13495},
}

@inproceedings{icml2018_adaptive_36496,
  title = {{Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1996},
}

@inproceedings{neurips2020_latent_60142,
  title = {{Latent Bandits Revisited}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18909},
}

@inproceedings{neurips2019_regret_58896,
  title = {{Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13948},
}

@inproceedings{iclr2018_deep_28640,
  title = {{Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/178},
}

@inproceedings{icml2020_thompson_38860,
  title = {{Thompson Sampling Algorithms for Mean-Variance Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6010},
}

@inproceedings{neurips2019_thompson_59086,
  title = {{Thompson Sampling and Approximate Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13933},
}

@inproceedings{aaai2022_a_1684,
  title = {{A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/06159-a-unifying-theory-of-thompson-sampling-for-continuous-risk-averse-bandits/},
}

@inproceedings{iclr2019_information_28850,
  title = {{Information-Directed Exploration for Deep Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/983},
}

@inproceedings{neurips2018_pg_57498,
  title = {{PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11455},
}

@inproceedings{neurips2021_bayesian_61352,
  title = {{Bayesian decision-making under misspecified priors with applications to meta-learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28280},
}

@inproceedings{icml2019_adaptive_37135,
  title = {{Adaptive Sensor Placement for Continuous Spaces}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4082},
}

@inproceedings{icml2021_mots_39584,
  title = {{MOTS: Minimax Optimal Thompson Sampling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9037},
}

@inproceedings{icml2021_optimal_39748,
  title = {{Optimal Thompson Sampling strategies for support-aware CVaR bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9315},
}

@inproceedings{neurips2020_statistical_60866,
  title = {{Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17644},
}

@inproceedings{aaai2024_the_7537,
  title = {{The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29240},
}

@inproceedings{icml2024_mathtt_44746,
  title = {{\$mathttVITS\$ : Variational Inference Thompson Sampling for contextual bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33706},
}

@inproceedings{neurips2024_thompson_71991,
  title = {{Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95322},
}

@inproceedings{neurips2024_towards_71993,
  title = {{Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95320},
}

@inproceedings{neurips2024_improved_73544,
  title = {{Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93935},
}

@inproceedings{neurips2025_constrained_78336,
  title = {{Constrained Linear Thompson Sampling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=daZ5x88IiE},
}

@inproceedings{iclr2024_only_35279,
  title = {{Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17794},
}

@inproceedings{icml2024_noise_44564,
  title = {{Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33888},
}

@inproceedings{icml2024_feel_45231,
  title = {{Feel-Good Thompson Sampling for Contextual Dueling Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33221},
}

@inproceedings{icml2024_bayesian_45306,
  title = {{Bayesian Regret Minimization in Offline Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33146},
}

@inproceedings{icml2025_zero_46556,
  title = {{Zero-Inflated Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46013},
}

@inproceedings{icml2025_connecting_46616,
  title = {{Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45953},
}

@inproceedings{icml2026_prior_50886,
  title = {{Prior Diffusiveness and Regret in the Linear-Gaussian Bandit}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=GeYKOC4BzB},
}

@inproceedings{icml2026_bfts_52783,
  title = {{BFTS: Thompson Sampling with Bayesian Additive Regression Trees}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Z1nbtKcLQk},
}

@inproceedings{neurips2024_improved_70593,
  title = {{Improved Regret of Linear Ensemble Sampling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96524},
}

@inproceedings{neurips2024_online_70714,
  title = {{Online Posterior Sampling with a Diffusion Prior}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96410},
}

@inproceedings{neurips2024_ensemble_72238,
  title = {{Ensemble sampling for linear bandits: small ensembles suffice}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95104},
}

@inproceedings{neurips2025_thompson_75046,
  title = {{Thompson Sampling for Multi-Objective Linear Contextual Bandit}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=3k1z56W015},
}

@inproceedings{neurips2025_contextual_76132,
  title = {{Contextual Thompson Sampling via Generation of Missing Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Fqsl9IfbfJ},
}

@inproceedings{neurips2025_adaptive_76324,
  title = {{Adaptive Variance Inflation in Thompson Sampling: Efficiency, Safety, Robustness, and Beyond}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=IBhxvINfxv},
}