Staber, Brian

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

NeurIPS 2023 MMGP: A Mesh Morphing Gaussian Process-Based Machine Learning Method for Regression of Physical Problems Under Nonparametrized Geometrical Variability Fabien Casenave, Brian Staber, Xavier Roynard