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^ Link to the paper ^ Title & Auteurs ^ Associated team (at most 2 students) ^ Comments ^
| [[paper 1|https://arxiv.org/abs/2004.10850]] | *A probabilistic approach to convex (φ)-entropy decay for Markov chains* — Giovanni Conforti | | |
| [[paper 2|https://arxiv.org/pdf/2412.17997]] | *Shifted Composition III: Local Error Framework for KL Divergence* — Jason M. Altschuler & Sinho Chewi | | |
| [[paper 3|https://arxiv.org/pdf/2011.10985]] | *A probability approximation framework: Markov process approach* — Peng Chen, Qi‑Man Shao & Lihu Xu | | |
| [[paper 4|https://arxiv.org/pdf/1801.07815]] | *Multivariate approximations in Wasserstein distance by Stein’s method and Bismut’s formula* — Xiao Fang, Qi‑Man Shao & Lihu Xu | | |
| [[paper 5|https://arxiv.org/pdf/2102.04923]] | *Berry–Es̈een Bounds for Multivariate Nonlinear Statistics with Applications to M‑estimators and Stochastic Gradient Descent Algorithms* — Qi‑Man Shao & Zhuo‐Song Zhang | | |
| [[paper 6|https://arxiv.org/abs/2308.16196]] | *Asymptotically unbiased approximation of the QSD of diffusion processes with a decreasing time step Euler scheme* — Fabien Panloup & Julien Reygner | | |
| [[paper 7|https://arxiv.org/abs/2412.09087]] | *General Markovian randomized equilibrium existence and construction in zero‑sum Dynkin games for diffusions* — Sören Christensen & Kristoffer Lindensjö | | |
| [[paper 8|https://arxiv.org/abs/2504.01247]] | *On spectral gap decomposition for Markov chains* — Qian Qin | | |
| [[paper 9|https://arxiv.org/abs/2410.08423]] | *A phase transition in sampling from Restricted Boltzmann Machines* — Youngwoo Kwon, Qian Qin, Guanyang Wang & Yuchen Wei | | |
| [[paper 10|https://arxiv.org/abs/2312.12782]] | *Spectral gap bounds for reversible hybrid Gibbs chains* — Qian Qin, Nianqiao Ju & Guanyang Wang | | |
| [[paper 11|https://arxiv.org/abs/2201.12500]] | *Analysis of two‑component Gibbs samplers using the theory of two projections* — Qian Qin | | |
| [[paper 12|https://arxiv.org/abs/1810.08826]] | *Wasserstein‑based methods for convergence complexity analysis of MCMC with applications* — Qian Qin & James P. Hobert | | |
| [[paper 13|https://arxiv.org/abs/2411.09514]] | *On importance sampling and independent Metropolis‑Hastings with an unbounded weight function* — George Deligiannidis, Pierre E. Jacob, El Mahdi Khribch & Guanyang Wang | | |
| [[paper 14|https://arxiv.org/abs/2501.18548]] | *The No‑Underrun Sampler: A Locally‑Adaptive, Gradient‑Free MCMC Method* — Nawaf Bou‑Rabee, Bob Carpenter, Sifan Liu & Stefan Oberdörster | | |
| [[paper 15|https://proceedings.neurips.cc/paper_files/paper/2024/file/99fecf765ecf62c3e3175ef2278f3315-Paper-Conference.pdf]] | *Deep Learning for Computing Convergence Rates of Markov Chains* — Y Qu et al. | | |
| [[paper 16|https://arxiv.org/pdf/2506.22258]] | *Mixing Time Bounds for the Gibbs Sampler under Isoperimetry* — Alexander Goyal, George Deligiannidis & Nikolas Kantas | | |
| [[paper 17|https://arxiv.org/abs/2102.00366]] | *Metropolis–Hastings transition kernel couplings* — John O’Leary & Guanyang Wang | | |

^ Link to the paper ^ Associated team (at most 2 students). To register, double click and fill your first name, your family name. And do the same for your classmate. ^ Comments ^ 
|[[paper 1|https://arxiv.org/abs/2004.10850]]  | | |
|https://arxiv.org/pdf/2412.17997  | | |
|https://arxiv.org/pdf/2011.10985  | | |
|https://arxiv.org/pdf/1801.07815  | | |
|https://arxiv.org/pdf/2102.04923  | | |
|https://arxiv.org/abs/2308.16196  | | |
|https://arxiv.org/abs/2412.09087  | | |
|https://arxiv.org/abs/2504.01247  | | |
|https://arxiv.org/abs/2410.08423  | | |
|https://arxiv.org/abs/2312.12782  | | |
|https://arxiv.org/abs/2201.12500  | | |
|https://arxiv.org/abs/1810.08826  | | |
|https://arxiv.org/abs/2411.09514  | | |
|https://arxiv.org/abs/2501.18548  | | |
|https://proceedings.neurips.cc/paper_files/paper/2024/file/99fecf765ecf62c3e3175ef2278f3315-Paper-Conference.pdf  | | |
|https://arxiv.org/pdf/2506.22258  | | |
| https://arxiv.org/abs/2102.00366  | | |

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