Lionel Riou-Durand 个人学术档案

20192020202120222023202417 26 36 57 75 43

开放获取的出版物数量

3 篇文章

0 篇文章

可查看的文章

无法查看的文章

根据资助方的强制性开放获取政策

Arnak S. DalalyanProfessor, ENSAE Paris(Ecole Nationale de la Statistique et de l'Administration Economique), IP在 ensae.fr 的电子邮件经过验证
Charles C MargossianResearch Fellow, Flatiron Institute在 flatironinstitute.org 的电子邮件经过验证
Avetik KaragulyanPostdoctoral fellow at KAUST在 kaust.edu.sa 的电子邮件经过验证
Nicolas ChopinProfessor of Statistics, ENSAE (Institut Polytechnique de Paris)在 ensae.fr 的电子邮件经过验证
Jure VogrincUniversity of Warwick在 warwick.ac.uk 的电子邮件经过验证
Matthew D. HoffmanResearch Scientist, Google Research在 google.com 的电子邮件经过验证
Aki VehtariProfessor, Aalto University在 aalto.fi 的电子邮件经过验证
Andrew GelmanProfessor of Statistics and Political Science, Columbia University在 stat.columbia.edu 的电子邮件经过验证

Lionel Riou-Durand

Assistant Professor, INSA Rouen

在 insa-rouen.fr 的电子邮件经过验证 - 首页


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
On sampling from a log-concave density using kinetic Langevin diffusions AS Dalalyan, L Riou-Durand	169	2020
Bounding the error of discretized Langevin algorithms for non-strongly log-concave targets AS Dalalyan, A Karagulyan, L Riou-Durand Journal of Machine Learning Research 23 (235), 1-38, 2022	47	2022
Noise contrastive estimation: Asymptotic properties, formal comparison with MC-MLE L Riou-Durand, N Chopin	16*	2018
Nested : Assessing the convergence of Markov chain Monte Carlo when running many short chains CC Margossian, MD Hoffman, P Sountsov, L Riou-Durand, A Vehtari, ... arXiv preprint arXiv:2110.13017, 2021	13	2021
Metropolis adjusted Langevin trajectories: a robust alternative to Hamiltonian Monte Carlo L Riou-Durand, J Vogrinc arXiv preprint arXiv:2202.13230, 2022	9	2022
Adaptive tuning for Metropolis adjusted Langevin trajectories L Riou-Durand, P Sountsov, J Vogrinc, C Margossian, S Power International Conference on Artificial Intelligence and Statistics, 8102-8116, 2023	4	2023
Theoretical contributions to Monte Carlo methods, and applications to Statistics L Riou-Durand Université Paris-Saclay, 2019		2019
Assessing the Convergence of Markov chain Monte Carlo when running many short chains CC Margossian, MD Hoffman, P Sountsov, L Riou-Durand, A Vehtari, ...
Bayesian inference using sub-posteriors. L Riou-Durand

系统目前无法执行此操作，请稍后再试。

文章 1–9

每年引用数