Meunier, Dimitri

10 publications

NeurIPS 2025 Demystifying Spectral Feature Learning for Instrumental Variable Regression Dimitri Meunier, Antoine Moulin, Jakub Wornbard, Vladimir R Kostic, Arthur Gretton

AISTATS 2025 Density Ratio-Based Proxy Causal Learning Without Density Ratios Bariscan Bozkurt, Ben Deaner, Dimitri Meunier, Liyuan Xu, Arthur Gretton

NeurIPS 2025 Density Ratio-Free Doubly Robust Proxy Causal Learning Bariscan Bozkurt, Houssam Zenati, Dimitri Meunier, Liyuan Xu, Arthur Gretton

ICLR 2025 Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Juno Kim, Dimitri Meunier, Arthur Gretton, Taiji Suzuki, Zhu Li

NeurIPS 2025 Regularized Least Squares Learning with Heavy-Tailed Noise Is Minimax Optimal Mattes Mollenhauer, Nicole Mücke, Dimitri Meunier, Arthur Gretton

NeurIPS 2024 Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li

NeurIPSW 2024 Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Juno Kim, Dimitri Meunier, Arthur Gretton, Taiji Suzuki, Zhu Li

JMLR 2024 Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton

ICML 2022 Distribution Regression with Sliced Wasserstein Kernels Dimitri Meunier, Massimiliano Pontil, Carlo Ciliberto

NeurIPS 2022 Optimal Rates for Regularized Conditional Mean Embedding Learning Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton