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world:projet-mda-2025
This is an old revision of the document!
| Link to the paper | Title & Auteurs | Associated team (at most 2 students) | Comments |
|---|---|---|---|
| https://arxiv.org/pdf/2004.10850.pdf | *A probabilistic approach to convex (φ)-entropy decay for Markov chains* — Giovanni Conforti | ||
| https://arxiv.org/pdf/2412.17997.pdf | *Shifted Composition III: Local Error Framework for KL Divergence* — Jason M. Altschuler & Sinho Chewi | ||
| https://arxiv.org/pdf/2011.10985.pdf | *A probability approximation framework: Markov process approach* — Peng Chen, Qi‑Man Shao & Lihu Xu | ||
| https://arxiv.org/pdf/1801.07815.pdf | *Multivariate approximations in Wasserstein distance by Stein’s method and Bismut’s formula* — Xiao Fang, Qi‑Man Shao & Lihu Xu | ||
| https://arxiv.org/pdf/2102.04923.pdf | *Berry–Es̈een Bounds for Multivariate Nonlinear Statistics with Applications to M‑estimators and Stochastic Gradient Descent Algorithms* — Qi‑Man Shao & Zhuo‐Song Zhang | ||
| https://arxiv.org/pdf/2308.16196.pdf | *Asymptotically unbiased approximation of the QSD of diffusion processes with a decreasing time step Euler scheme* — Fabien Panloup & Julien Reygner | ||
| https://arxiv.org/pdf/2412.09087.pdf | *General Markovian randomized equilibrium existence and construction in zero‑sum Dynkin games for diffusions* — Sören Christensen & Kristoffer Lindensjö | ||
| https://arxiv.org/pdf/2504.01247.pdf | *On spectral gap decomposition for Markov chains* — Qian Qin | ||
| https://arxiv.org/pdf/2410.08423.pdf | *A phase transition in sampling from Restricted Boltzmann Machines* — Youngwoo Kwon, Qian Qin, Guanyang Wang & Yuchen Wei | ||
| https://arxiv.org/pdf/2312.12782.pdf | *Spectral gap bounds for reversible hybrid Gibbs chains* — Qian Qin, Nianqiao Ju & Guanyang Wang | ||
| https://arxiv.org/pdf/2201.12500.pdf | *Analysis of two‑component Gibbs samplers using the theory of two projections* — Qian Qin | ||
| https://arxiv.org/pdf/1810.08826.pdf | *Wasserstein‑based methods for convergence complexity analysis of MCMC with applications* — Qian Qin & James P. Hobert | ||
| https://arxiv.org/pdf/2411.09514.pdf | *On importance sampling and independent Metropolis‑Hastings with an unbounded weight function* — George Deligiannidis, Pierre E. Jacob, El Mahdi Khribch & Guanyang Wang | ||
| https://arxiv.org/pdf/2501.18548.pdf | *The No‑Underrun Sampler: A Locally‑Adaptive, Gradient‑Free MCMC Method* — Nawaf Bou‑Rabee, Bob Carpenter, Sifan Liu & Stefan Oberdörster | ||
| 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. | ||
| https://arxiv.org/pdf/2506.22258.pdf | *Mixing Time Bounds for the Gibbs Sampler under Isoperimetry* — Alexander Goyal, George Deligiannidis & Nikolas Kantas | ||
| https://arxiv.org/pdf/2102.00366.pdf | *Metropolis–Hastings transition kernel couplings* — John O’Leary & Guanyang Wang |
| Link to the paper | Title & Auteurs | Associated team (at most 2 students) | Comments |
|---|---|---|---|
| https://arxiv.org/abs/2004.10850 | *A probabilistic approach to convex (φ)-entropy decay for Markov chains* — Giovanni Conforti | ||
| https://arxiv.org/pdf/2412.17997 | *Shifted Composition III: Local Error Framework for KL Divergence* — Jason M. Altschuler & Sinho Chewi | ||
| https://arxiv.org/pdf/2011.10985 | *A probability approximation framework: Markov process approach* — Peng Chen, Qi‑Man Shao & Lihu Xu | ||
| 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 | ||
| 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 | ||
| 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 | ||
| https://arxiv.org/abs/2412.09087 | *General Markovian randomized equilibrium existence and construction in zero‑sum Dynkin games for diffusions* — Sören Christensen & Kristoffer Lindensjö | ||
| https://arxiv.org/abs/2504.01247 | *On spectral gap decomposition for Markov chains* — Qian Qin | ||
| https://arxiv.org/abs/2410.08423 | *A phase transition in sampling from Restricted Boltzmann Machines* — Youngwoo Kwon, Qian Qin, Guanyang Wang & Yuchen Wei | ||
| https://arxiv.org/abs/2312.12782 | *Spectral gap bounds for reversible hybrid Gibbs chains* — Qian Qin, Nianqiao Ju & Guanyang Wang | ||
| https://arxiv.org/abs/2201.12500 | *Analysis of two‑component Gibbs samplers using the theory of two projections* — Qian Qin | ||
| https://arxiv.org/abs/1810.08826 | *Wasserstein‑based methods for convergence complexity analysis of MCMC with applications* — Qian Qin & James P. Hobert | ||
| 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 | ||
| 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 | ||
| 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. | ||
| https://arxiv.org/pdf/2506.22258 | *Mixing Time Bounds for the Gibbs Sampler under Isoperimetry* — Alexander Goyal, George Deligiannidis & Nikolas Kantas | ||
| 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 |
|---|---|---|
| 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 |
world/projet-mda-2025.1762336583.txt.gz · Last modified: 2025/11/05 10:56 by rdouc
