| 2024 | AISTATS | Stochastic Approximation with Biased MCMC for Expectation Maximization. | Samuel Gruffaz, Kyurae Kim, Alain Durmus, Jacob R. Gardner |
| 2024 | AISTATS | Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training. | Tom Sander, Maxime Sylvestre, Alain Durmus |
| 2023 | AISTATS | Tight Regret and Complexity Bounds for Thompson Sampling via Langevin Monte Carlo. | Tom Huix, Matthew Zhang, Alain Durmus |
| 2023 | AISTATS | Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. | Vincent Plassier, Eric Moulines, Alain Durmus |
| 2023 | COLT | Non-asymptotic convergence bounds for Sinkhorn iterates and their gradients: a coupling approach. | Giacomo Greco, Maxence Noble, Giovanni Conforti, Alain Durmus |
| 2022 | AISTATS | QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. | Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines |
| 2021 | AISTATS | On Riemannian Stochastic Approximation Schemes with Fixed Step-Size. | Alain Durmus, Pablo Jimnez, Eric Moulines, Salem Said |
| 2021 | COLT | On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. | Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai |
| 2021 | COLT | Convergence rates and approximation results for SGD and its continuous-time counterpart. | Xavier Fontaine, Valentin De Bortoli, Alain Durmus |
| 2021 | ICML | DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs. | Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines |
| 2021 | ICML | Monte Carlo Variational Auto-Encoders. | Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov |
| 2020 | ICASSP | Approximate Bayesian Computation with the Sliced-Wasserstein Distance. | Kimia Nadjahi, Valentin De Bortoli, Alain Durmus, Roland Badeau, Umut Simsekli |
| 2019 | ICML | Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. | Antoine Liutkus, Umut Simsekli, Szymon Majewski, Alain Durmus, Fabian-Robert Stter |
| 2017 | COLT | Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo. | Nicolas Brosse, Alain Durmus, Eric Moulines, Marcelo Pereyra |
| 2017 | ICASSP | Parallelized Stochastic Gradient Markov Chain Monte Carlo algorithms for non-negative matrix factorization. | Umut Simsekli, Alain Durmus, Roland Badeau, Gal Richard, Eric Moulines, A. Taylan Cemgil |
| 2013 | CRYPTO | Lattice Signatures and Bimodal Gaussians. | Lo Ducas, Alain Durmus, Tancrde Lepoint, Vadim Lyubashevsky |
| 2012 | PKC | Ring-LWE in Polynomial Rings. | Lo Ducas, Alain Durmus |