Risk bounds when learning infinitely many response functions by ordinary linear regression. - Vincent Plassier; François Portier; Johan Segers (CoRR, 2020)

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 (ICML, 2021)

DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm. - Vincent Plassier; Maxime Vono; Alain Durmus; Eric Moulines (CoRR, 2021)

QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. - Maxime Vono; Vincent Plassier; Alain Durmus; Aymeric Dieuleveut; Eric Moulines (AISTATS, 2022)

Membership Inference Attacks via Adversarial Examples. - Hamid Jalalzai; Elie Kadoche; Rémi Leluc; Vincent Plassier (CoRR, 2022)

Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. - Vincent Plassier; Eric Moulines; Alain Durmus (AISTATS, 2023)

Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. - Vincent Plassier; Mehdi Makni; Aleksandr Rubashevskii; Eric Moulines; Maxim Panov (ICML, 2023)

Efficient Conformal Prediction under Data Heterogeneity. - Vincent Plassier; Nikita Kotelevskii; Aleksandr Rubashevskii; Fedor Noskov; Maksim Velikanov; Alexander Fishkov; Samuel Horváth; Martin Takác 001; Eric Moulines; Maxim Panov (AISTATS, 2024)

Conditionally valid Probabilistic Conformal Prediction. - Vincent Plassier; Alexander Fishkov; Maxim Panov; Eric Moulines (CoRR, 2024)

Probabilistic Conformal Prediction with Approximate Conditional Validity. - Vincent Plassier; Alexander Fishkov; Mohsen Guizani; Maxim Panov; Eric Moulines (ICLR, 2025)

Rectifying Conformity Scores for Better Conditional Coverage. - Vincent Plassier; Alexander Fishkov; Victor Dheur; Mohsen Guizani; Souhaib Ben Taieb; Maxim Panov; Eric Moulines (CoRR, 2025)