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  author = {Dalalyan, Arnak S.},
  title = {Theoretical Guarantees for Approximate Sampling from Smooth and Log-Concave Densities},
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}

@article{durmus2017langevin,
  author = {Durmus, Alain and Moulines, Eric},
  title = {Nonasymptotic Convergence Analysis for the Unadjusted {Langevin} Algorithm},
  journal = {The Annals of Applied Probability},
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  year = {2017},
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}

@inproceedings{cheng2018underdamped,
  author = {Cheng, Xiang and Chatterji, Niladri S. and Bartlett, Peter L. and Jordan, Michael I.},
  title = {Underdamped {Langevin} {MCMC}: A Non-Asymptotic Analysis},
  booktitle = {Proceedings of the 31st Conference on Learning Theory},
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  pages = {300--323},
  year = {2018},
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}

@inproceedings{shen2019randomized,
  author = {Shen, Ruoqi and Lee, Yin Tat},
  title = {The Randomized Midpoint Method for Log-Concave Sampling},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {32},
  year = {2019},
  url = {https://proceedings.neurips.cc/paper/2019/hash/eb86d510361fc23b59f18c1bc9802cc6-Abstract.html}
}

@inproceedings{lee2021proximal,
  author = {Lee, Yin Tat and Shen, Ruoqi and Tian, Kevin},
  title = {Structured Logconcave Sampling with a Restricted {Gaussian} Oracle},
  booktitle = {Proceedings of the 34th Conference on Learning Theory},
  series = {Proceedings of Machine Learning Research},
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  pages = {2993--3050},
  year = {2021},
  note = {Revised version: arXiv:2010.03106v4},
  url = {https://arxiv.org/abs/2010.03106v4}
}

@inproceedings{chen2022proximal,
  author = {Chen, Yongxin and Chewi, Sinho and Salim, Adil and Wibisono, Andre},
  title = {Improved Analysis for a Proximal Algorithm for Sampling},
  booktitle = {Proceedings of the 35th Conference on Learning Theory},
  series = {Proceedings of Machine Learning Research},
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  pages = {2984--3014},
  year = {2022},
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}

@article{chewi2023lower,
  author = {Chewi, Sinho and de Dios Pont, Jaume and Li, Jerry and Lu, Chen and Narayanan, Shyam},
  title = {Query Lower Bounds for Log-Concave Sampling},
  journal = {Journal of the ACM},
  volume = {71},
  number = {4},
  pages = {29:1--29:42},
  year = {2024},
  doi = {10.1145/3673651},
  note = {First circulated in 2023; theorem numbering cited from arXiv:2304.02599v2},
  url = {https://arxiv.org/abs/2304.02599v2}
}

@inproceedings{altschuler2026shifted,
  author = {Altschuler, Jason M. and Chewi, Sinho and Zhang, Matthew S.},
  title = {Shifted Composition {IV}: Toward Ballistic Acceleration for Log-Concave Sampling},
  booktitle = {Proceedings of the 58th Annual ACM Symposium on Theory of Computing},
  pages = {1739--1750},
  publisher = {Association for Computing Machinery},
  year = {2026},
  doi = {10.1145/3798129.3800881},
  note = {Full version: arXiv:2506.23062v3},
  url = {https://arxiv.org/abs/2506.23062v3}
}

@misc{chen2026exact,
  author = {Chen, Fan and Chewi, Sinho and Rakhlin, Alexander and Zhang, Matthew S.},
  title = {Exact Simulation of Diffusions and Improved Algorithms for Log-Concave Sampling},
  year = {2026},
  eprint = {2608.05022},
  archivePrefix = {arXiv},
  primaryClass = {cs.DS},
  note = {Version 1, August 5, 2026},
  url = {https://arxiv.org/abs/2608.05022v1}
}

@misc{chen2026picard,
  author = {Chen, Fan and Chewi, Sinho and Lu, Jianfeng and Zhang, Matthew S.},
  title = {Smoothed {Picard} {Hamiltonian} {Monte Carlo}},
  year = {2026},
  eprint = {2609.06906},
  archivePrefix = {arXiv},
  primaryClass = {math.ST},
  note = {Version 1, September 7, 2026},
  url = {https://arxiv.org/abs/2609.06906v1}
}

@misc{chen2026bps,
  author = {Chen, Fan and Chewi, Sinho and Lu, Jianfeng and Zhang, Matthew S.},
  title = {Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler},
  year = {2026},
  eprint = {2609.06905},
  archivePrefix = {arXiv},
  primaryClass = {math.ST},
  note = {Version 1, September 7, 2026},
  url = {https://arxiv.org/abs/2609.06905v1}
}

@misc{chen2026cloud,
  author = {Chen, Fan and Chewi, Sinho and Lu, Jianfeng and Zhang, Matthew S.},
  title = {High-Accuracy Simulation of {Picard HMC}, Part {I}: {Gaussian} Cloud Correction},
  year = {2026},
  eprint = {2609.38710},
  archivePrefix = {arXiv},
  primaryClass = {math.ST},
  note = {Version 1, September 30, 2026},
  url = {https://arxiv.org/abs/2609.38710v1}
}

@misc{chen2026divergence,
  author = {Chen, Fan and Chewi, Sinho and Lu, Jianfeng and Zhang, Matthew S.},
  title = {Sharp {Gaussian} Divergence and {Bernstein--Markov} Inequalities},
  year = {2026},
  eprint = {2609.32851},
  archivePrefix = {arXiv},
  primaryClass = {math.PR},
  note = {Version 1, September 26, 2026},
  url = {https://arxiv.org/abs/2609.32851v1}
}

@inproceedings{song2021score,
  author = {Song, Yang and Sohl-Dickstein, Jascha and Kingma, Diederik P. and Kumar, Abhishek and Ermon, Stefano and Poole, Ben},
  title = {Score-Based Generative Modeling through Stochastic Differential Equations},
  booktitle = {International Conference on Learning Representations},
  year = {2021},
  url = {https://arxiv.org/abs/2011.13456v2}
}

@article{albergo2025interpolants,
  author = {Albergo, Michael S. and Boffi, Nicholas M. and Vanden-Eijnden, Eric},
  title = {Stochastic Interpolants: A Unifying Framework for Flows and Diffusions},
  journal = {Journal of Machine Learning Research},
  volume = {26},
  number = {209},
  pages = {1--80},
  year = {2025},
  note = {Equation numbering cited from arXiv:2303.08797v4},
  url = {https://jmlr.org/papers/v26/23-1605.html}
}

@book{bakry2014analysis,
  author = {Bakry, Dominique and Gentil, Ivan and Ledoux, Michel},
  title = {Analysis and Geometry of {Markov} Diffusion Operators},
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@article{courtade2019stein,
  author = {Courtade, Thomas A. and Fathi, Max and Pananjady, Ashwin},
  title = {Existence of {Stein} Kernels under a Spectral Gap, and Discrepancy Bounds},
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@misc{lee2018odes,
  author = {Lee, Yin Tat and Song, Zhao and Vempala, Santosh S.},
  title = {Algorithmic Theory of {ODEs} and Sampling from Well-Conditioned Logconcave Densities},
  year = {2018},
  eprint = {1812.06243},
  archivePrefix = {arXiv},
  note = {Version 1, December 15, 2018},
  url = {https://arxiv.org/abs/1812.06243v1}
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@misc{mangoubi2017rapid,
  author = {Mangoubi, Oren and Smith, Aaron},
  title = {Rapid Mixing of {Hamiltonian} {Monte Carlo} on Strongly Log-Concave Distributions},
  year = {2017},
  eprint = {1708.07114},
  archivePrefix = {arXiv},
  note = {Version 1, August 23, 2017},
  url = {https://arxiv.org/abs/1708.07114v1}
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@article{anshelevich2004appell,
  author = {Anshelevich, Michael},
  title = {{Appell} Polynomials and Their Relatives},
  journal = {International Mathematics Research Notices},
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@article{adamczak2015concentration,
  author = {Adamczak, Rados{\l}aw and Wolff, Pawe{\l}},
  title = {Concentration Inequalities for Non-{Lipschitz} Functions with Bounded Derivatives of Higher Order},
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@misc{kothari2017agnostic,
  author = {Kothari, Pravesh K. and Steinhardt, Jacob},
  title = {Better Agnostic Clustering via Relaxed Tensor Norms},
  year = {2017},
  eprint = {1711.07465},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  note = {Version 1, November 20, 2017},
  url = {https://arxiv.org/abs/1711.07465v1}
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@inproceedings{ma2015recipe,
  author = {Ma, Yi-An and Chen, Tianqi and Fox, Emily B.},
  title = {A Complete Recipe for Stochastic Gradient {MCMC}},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {28},
  year = {2015},
  url = {https://proceedings.neurips.cc/paper/2015/hash/9a4400501febb2a95e79248486a5f6d3-Abstract.html}
}