| 2025 | AISTATS | Distribution-Aware Mean Estimation under User-level Local Differential Privacy. | Corentin Pla, Maxime Vono, Hugo Richard |
| 2024 | WISE | Open Research Challenges for Private Advertising Systems Under Local Differential Privacy. | Matilde Tullii, Solenne Gaucher, Hugo Richard, Eustache Diemert, Vianney Perchet, Alain Rakotomamonjy, Clment Calauznes, Maxime Vono |
| 2022 | AISTATS | QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. | Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines |
| 2022 | KDD | Reward Optimizing Recommendation using Deep Learning and Fast Maximum Inner Product Search. | Imad Aouali, Amine Benhalloum, Martin Bompaire, Achraf Ait Sidi Hammou, Sergey Ivanov, Benjamin Heymann, David Rohde, Otmane Sakhi, Flavian Vasile, Maxime Vono |
| 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 |
| 2019 | ICASSP | Bayesian Image Restoration under Poisson Noise and Log-concave Prior. | Maxime Vono, Nicolas Dobigeon, Pierre Chainais |
| 2019 | ICASSP | Efficient Sampling through Variable Splitting-inspired Bayesian Hierarchical Models. | Maxime Vono, Nicolas Dobigeon, Pierre Chainais |