Sliced-Wasserstein normalizing flows: beyond maximum likelihood training. - Florentin Coeurdoux; Nicolas Dobigeon; Pierre Chainais (ESANN, 2022)

Learning Optimal Transport Between Two Empirical Distributions with Normalizing Flows. - Florentin Coeurdoux; Nicolas Dobigeon; Pierre Chainais (ECML/PKDD (5), 2022)

Monte Carlo sampling and deep generative models for Bayesian inference. (Echantillonnage Monte Carlo et modèles génératifs profonds pour inférence Bayésienne). - Florentin Coeurdoux (2023)

Plug-and-Play Split Gibbs Sampler: Embedding Deep Generative Priors in Bayesian Inference. - Florentin Coeurdoux; Nicolas Dobigeon; Pierre Chainais (IEEE Trans. Image Process., 2024)

Normalizing flow sampling with Langevin dynamics in the latent space. - Florentin Coeurdoux; Nicolas Dobigeon; Pierre Chainais (Mach. Learn., 2024)

Multitask Learning with Stochastic Interpolants. - Hugo Negrel; Florentin Coeurdoux; Michael S. Albergo; Eric Vanden-Eijnden (CoRR, 2025)