Brian Staber

According to our database, Brian Staber authored at least 7 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Learning signals defined on graphs with optimal transport and Gaussian process regression.

Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber

CoRR, 2024

Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels.

Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability.

Fabien Casenave, Brian Staber, Xavier Roynard

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization.

Clément Bénard, Brian Staber, Sébastien Da Veiga

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Quantitative performance evaluation of Bayesian neural networks.

Brian Staber, Sébastien Da Veiga

CoRR, 2022

2015

Approximate Solutions of Lagrange Multipliers for Information-Theoretic Random Field Models.

Brian Staber, Johann Guilleminot

SIAM/ASA J. Uncertain. Quantification, 2015