most citedA Gaussian process and linear-based framework for computing cut distributions in modular Bayesian calibration of two chained computer models

1 citations · 1 across the 1 of their papers we have counts for

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stat.CO2026★ 1 cited

A Gaussian process and linear-based framework for computing cut distributions in modular Bayesian calibration of two chained computer models

Oumar Baldé, Guillaume Damblin, Amandine Marrel +2

Computer models are widely used in science and engineering to simulate complex systems. However, these models are affected by several sources of uncertainty, which may limit their…

stat.ML2026

Multivariate Bayesian Last Layer for Regression with Uncertainty Quantification and Decomposition

Han Wang, Eiji Kawasaki, Guillaume Damblin +1

We present new Bayesian Last Layer neural network models in the setting of multivariate regression under heteroscedastic noise, and propose EM algorithms for parameter learning. Ba…