Brian Staber

4 papers · 2023–2025 · 2 venues · across top CS/AI venues

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Achievements

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🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (10)

Venues

AISTATS (2) NeurIPS (2)

Top co-authors

Sébastien Da Veiga (3) Josselin Garnier (2) Raphaël Carpintero Perez (2) Clement Benard (1) Fabien Casenave (1) Xavier Roynard (1)

Research topics

Machine Learning (4) Bayesian & Probabilistic · Machine Learning (4) Optimization & Theory (3) Core Methods (2) Learning Types (2) Artificial Intelligence (1) Mathematics & Optimization (1) Bayesian & Probabilistic · Artificial Intelligence (1) Optimization (1)

Keywords

uncertainty quantification (2) gaussian process regression (2) bayesian inference (1) optimal transport (1) markov chain monte carlo (1) dimension reduction (1) gaussian process (1) graph regression (1) graph kernel (1) graph signal (1) predictive uncertainty (1) sliced wasserstein (1) weisfeiler-lehman graph kernel (1) computational physics (1) positive definiteness (1) kernel stein discrepancy (1) physical simulation (1) stein thinning (1) active learning (1) mesh morphing (1)

Papers

Learning signals defined on graphs with optimal transport and Gaussian process regression AISTATS 2025 Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels AISTATS 2024 Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization NeurIPS 2023 MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability NeurIPS 2023