Alain Oliviero Durmus

27 papers A* 16A 2Journal 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance.
CoRR
Ahmed Ghorbel, Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati
2025 A* conf
A Mixture-Based Framework for Guiding Diffusion Models.
ICML
Yazid Janati, Badr Moufad, Mehdi Abou El Qassime, Alain Oliviero Durmus, Eric Moulines, Jimmy Olsson
2025 J jnl
Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped.
CoRR
Kyurae Kim, Samuel Gruffaz, Ji Won Park, Alain Oliviero Durmus
2025 A* conf
Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms.
ICML
Andrea Bertazzi, Tim Johnston, Gareth O. Roberts, Alain Oliviero Durmus
2025 A* conf
Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions.
ICML
Le-Tuyet-Nhi Pham, Dario Shariatian, Antonio Ocello, Giovanni Conforti, Alain Oliviero Durmus
2025 J jnl
Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance.
CoRR
Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati
2025 A* conf
Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models.
ICLR
Dario Shariatian, Umut Simsekli, Alain Oliviero Durmus
2025 A* conf
Learned Reference-based Diffusion Sampler for multi-modal distributions.
ICLR
Maxence Noble, Louis Grenioux, Marylou Gabrié, Alain Oliviero Durmus
2025 A* conf
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation.
ICLR
Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov
2025 A conf
Personalized Convolutional Dictionary Learning of Physiological Time Series.
AISTATS
Axel Roques, Samuel Gruffaz, Kyurae Kim, Alain Oliviero Durmus, Laurent Oudre
2025 J jnl
Personalized Convolutional Dictionary Learning of Physiological Time Series.
CoRR
Axel Roques, Samuel Gruffaz, Kyurae Kim, Alain Oliviero Durmus, Laurent Oudre
2025 A* conf
Prediction-Aware Learning in Multi-Agent Systems.
ICML
Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Oliviero Durmus
2025 A conf
Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation.
AISTATS
Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines
2025 A* conf
Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up.
ICML
Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Eric Moulines
2025 A* conf
Variational Diffusion Posterior Sampling with Midpoint Guidance.
ICLR
Badr Moufad, Yazid Janati, Lisa Bedin, Alain Oliviero Durmus, Randal Douc, Eric Moulines, Jimmy Olsson
2025 A* conf
Watermark Anything With Localized Messages.
ICLR
Tom Sander, Pierre Fernandez, Alain Oliviero Durmus, Teddy Furon, Matthijs Douze
2024 A* conf
Differentially Private Representation Learning via Image Captioning.
ICML
Tom Sander, Yaodong Yu, Maziar Sanjabi, Alain Oliviero Durmus, Yi Ma, Kamalika Chaudhuri, Chuan Guo
2024 A* conf
Incentivized Learning in Principal-Agent Bandit Games.
ICML
Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, Eric Moulines, Michael I. Jordan, El-Mahdi El-Mhamdi, Alain Oliviero Durmus
2024 J jnl
Learned Reference-based Diffusion Sampling for multi-modal distributions.
CoRR
Maxence Noble, Louis Grenioux, Marylou Gabrié, Alain Oliviero Durmus
2024 J jnl
Piecewise deterministic generative models.
CoRR
Andrea Bertazzi, Alain Oliviero Durmus, Dario Shariatian, Umut Simsekli, Eric Moulines
2024 J jnl
Stochastic Approximation with Biased MCMC for Expectation Maximization.
CoRR
Samuel Gruffaz, Kyurae Kim, Alain Oliviero Durmus, Jacob R. Gardner
2024 A* conf
Stochastic Localization via Iterative Posterior Sampling.
ICML
Louis Grenioux, Maxence Noble, Marylou Gabrié, Alain Oliviero Durmus
2024 J jnl
Stochastic Localization via Iterative Posterior Sampling.
CoRR
Louis Grenioux, Maxence Noble, Marylou Gabrié, Alain Oliviero Durmus
2024 A* conf
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians.
ICML
Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines
2024 A* conf
VITS : Variational Inference Thompson Sampling for contextual bandits.
ICML
Pierre Clavier, Tom Huix, Alain Oliviero Durmus
2023 A* conf
On Sampling with Approximate Transport Maps.
ICML
Louis Grenioux, Alain Oliviero Durmus, Eric Moulines, Marylou Gabrié
2023 J jnl
Second order quantitative bounds for unadjusted generalized Hamiltonian Monte Carlo.
CoRR
Evan Camrud, Alain Oliviero Durmus, Pierre Monmarché, Gabriel Stoltz