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07/25/2023
Rational kernel-based interpolation for complex-valued frequency response functions
This work is concerned with the kernel-based approximation of a complex-...
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11/02/2022
Bayesian sequential design of computer experiments to estimate reliable sets
We consider an unknown multivariate function representing a system-such ...
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07/08/2022
Bayesian multi-objective optimization for stochastic simulators: an extension of the Pareto Active Learning method
This article focuses on the multi-objective optimization of stochastic s...
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06/07/2022
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
This work presents a new procedure for obtaining predictive distribution...
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03/01/2022
Integration of bounded monotone functions: Revisiting the nonsequential case, with a focus on unbiased Monte Carlo (randomized) methods
In this article we revisit the problem of numerical integration for mono...
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07/13/2021
Gaussian process interpolation: the choice of the family of models is more important than that of the selection criterion
This article revisits the fundamental problem of parameter selection for...
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03/25/2021
On the quantification of discretization uncertainty: comparison of two paradigms
Numerical models based on partial differential equations (PDE), or integ...
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01/24/2021
Numerical issues in maximum likelihood parameter estimation for Gaussian process regression
This article focuses on numerical issues in maximum likelihood parameter...
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07/27/2020
Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction
This article deals with the sequential design of experiments for (determ...
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02/26/2020
Towards new cross-validation-based estimators for Gaussian process regression: efficient adjoint computation of gradients
We consider the problem of estimating the parameters of the covariance f...
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09/14/2018
User preferences in Bayesian multi-objective optimization: the expected weighted hypervolume improvement criterion
In this article, we present a framework for taking into account user pre...
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09/20/2017
Integrating hyper-parameter uncertainties in a multi-fidelity Bayesian model for the estimation of a probability of failure
A multi-fidelity simulator is a numerical model, in which one of the inp...
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07/26/2017
Sequential design of experiments to estimate a probability of exceeding a threshold in a multi-fidelity stochastic simulator
In this article, we consider a stochastic numerical simulator to assess ...
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08/03/2016
A supermartingale approach to Gaussian process based sequential design of experiments
Gaussian process (GP) models have become a well-established frameworkfor...
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10/02/2015
A Bayesian approach to constrained single- and multi-objective optimization
This article addresses the problem of derivative-free (single- or multi-...
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01/15/2015
