Optimistic Planning by Regularized Dynamic Programming. - Antoine Moulin; Gergely Neu (ICML, 2023)

Spectral Representation for Causal Estimation with Hidden Confounders. - Haotian Sun; Antoine Moulin; Tongzheng Ren; Arthur Gretton; Bo Dai 001 (AISTATS, 2025)

Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning. - Antoine Moulin; Gergely Neu; Luca Viano (COLT, 2025)

Inverse Q-Learning Done Right: Offline Imitation Learning in Qπ-Realizable MDPs. - Antoine Moulin; Gergely Neu; Luca Viano (CoRR, 2025)

When Lower-Order Terms Dominate: Adaptive Expert Algorithms for Heavy-Tailed Losses. - Antoine Moulin; Emmanuel Esposito; Dirk van der Hoeven (CoRR, 2025)

Demystifying Spectral Feature Learning for Instrumental Variable Regression. - Dimitri Meunier; Antoine Moulin; Jakub Wornbard; Vladimir R. Kostic; Arthur Gretton (CoRR, 2025)