Garnier, Josselin

6 publications

AISTATS 2025 Learning Signals Defined on Graphs with Optimal Transport and Gaussian Process Regression Raphael Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber

NeurIPS 2025 Preconditioned Langevin Dynamics with Score-Based Generative Models for Infinite-Dimensional Linear Bayesian Inverse Problems Lorenzo Baldassari, Josselin Garnier, Knut Solna, Maarten V. de Hoop

AISTATS 2024 Gaussian Process Regression with Sliced Wasserstein Weisfeiler-Lehman Graph Kernels Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber

ICML 2023 Comparison of Meta-Learners for Estimating Multi-Valued Treatment Heterogeneous Effects Naoufal Acharki, Ramiro Lugo, Antoine Bertoncello, Josselin Garnier

NeurIPS 2023 Conditional Score-Based Diffusion Models for Bayesian Inference in Infinite Dimensions Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop

MLJ 2015 Asymptotic Analysis of the Learning Curve for Gaussian Process Regression Loïc Le Gratiet, Josselin Garnier