Da Veiga, Sébastien

5 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 Scalable and Adaptive Prediction Bands with Kernel Sum-of-Squares Louis Allain, Sébastien Da Veiga, Brian Staber

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

NeurIPS 2023 Kernel Stein Discrepancy Thinning: A Theoretical Perspective of Pathologies and a Practical Fix with Regularization Clement Benard, Brian Staber, Sébastien Da Veiga

AISTATS 2022 SHAFF: Fast and Consistent SHApley eFfect Estimates via Random Forests Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet