324 citations · 635 across the 25 of their papers we have counts for
9 papers · 1 filter
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
Sébastien Petit, Julien Bect, Emmanuel Vazquez
This work presents a new procedure for obtaining predictive distributions in the context of Gaussian process (GP) modeling, with a relaxation of the interpolation constraints outsi…
Towards new cross-validation-based estimators for Gaussian process regression: efficient adjoint computation of gradients
Sébastien Petit, Julien Bect, Sébastien da Veiga +2
We consider the problem of estimating the parameters of the covariance function of a Gaussian process by cross-validation. We suggest using new cross-validation criteria derived fr…
Sequential design of experiments to estimate a probability of exceeding a threshold in a multi-fidelity stochastic simulator
Rémi Stroh, Séverine Demeyer, Nicolas Fischer +2
In this article, we consider a stochastic numerical simulator to assess the impact of some factors on a phenomenon. The simulator is seen as a black box with inputs and outputs. Th…
Bayesian subset simulation
Julien Bect, Ling Li, Emmanuel Vazquez
We consider the problem of estimating a probability of failure , defined as the volume of the excursion set of a function …
A Bayesian approach to constrained single- and multi-objective optimization
Paul Feliot, Julien Bect, Emmanuel Vazquez
This article addresses the problem of derivative-free (single- or multi-objective) optimization subject to multiple inequality constraints. Both the objective and constraint functi…
A new integral loss function for Bayesian optimization
Emmanuel Vazquez, Julien Bect
We consider the problem of maximizing a real-valued continuous function using a Bayesian approach. Since the early work of Jonas Mockus and Antanas Žilinskas in the 70's, the p…