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hal-01565514v2  Preprints, Working Papers, ...
Aymeric Dieuleveut, Alain Durmus, Francis Bach. Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains
2018
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hal-02626383v2  Preprints, Working Papers, ...
Alain Durmus, Pablo Jiménez, Eric Moulines, Salem Said, Hoi-To Wai. Convergence Analysis of Riemannian Stochastic Approximation Schemes
2020
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hal-01267115v1  Journal articles
Alain Durmus, Éric Moulines, Marcelo Pereyra. Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau.
SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2018, 11 (1)
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hal-01648666v2  Journal articles
Nicolas Brosse, Alain Durmus, Éric Moulines. Normalizing constants of log-concave densities
Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2018, 12 (1), pp.851-889. ⟨10.1214/18-EJS1411⟩
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hal-02191302v1  Conference papers
Antoine Liutkus, Umut Imşekli, Szymon Majewski, Alain Durmus, Fabian-Robert Stöter. Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
36th International Conference on Machine Learning (ICML), Jun 2019, Long Beach, United States
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hal-01934291v1  Conference papers
Nicolas Brosse, Alain Durmus, Éric Moulines. The promises and pitfalls of Stochastic Gradient Langevin Dynamics
NeurIPS 2018 (Advances in Neural Information Processing Systems 2018), Dec 2018, Montreal, France