J. Bect

发表

Convergence properties of the expected improvement algorithm with fixed mean and covariance functions

E. Vázquez, J. Bect, 2007, 0712.3744.

Convergence properties of the expected improvement algorithm

E. Vázquez, J. Bect, 2007, 0712.3744.

A unifying formulation of the Fokker–Planck–Kolmogorov equation for general stochastic hybrid systems

J. Bect, Julien Bect, 2008, 0801.3725.

A l1-Unified Variational Framework for Image Restoration

Antonin Chambolle, Gilles Aubert, Julien Bect, 2004, ECCV.

A supermartingale approach to Gaussian process based sequential design of experiments

J. Bect, D. Ginsbourger, F. Bachoc, 2016, Bernoulli.

On the Fokker-Planck Equation for Stochastic Hybrid Systems: Application to a Wind Turbine Model

J. Bect, H. Baili, Y. Phulpin, 2006, 2006 International Conference on Probabilistic Methods Applied to Power Systems.

Note on the computation of the Metropolis-Hastings ratio for Birth-or-Death moves in trans-dimensional MCMC algorithms for signal decomposition problems

Julien Bect, Gilles Fleury, Alireza Roodaki, 2011 .

Perturbed-Law based sensitivity Indices for sensitivity analysis in structural reliability

J. Bect, N. Bousquet, B. Iooss, 2016 .

A Bayesian subset simulation approach to constrained global optimization of expensive-to-evaluate black-box functions

E. Vázquez, J. Bect, Paul Feliot, 2014 .

Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization

E. Vázquez, J. Bect, S. Petit, 2022, 2206.03034.

On the convergence of the expected improvement algorithm

Julien Bect, Emmanuel Vazquez, E. Vázquez, 2007 .

Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization

E. Vázquez, J. Bect, S. Petit, 2022, 2206.03034.

Quantifying and reducing uncertainties on excursion sets under a gaussian random field prior

David Ginsbourger, Julien Bect, Ilya Molchanov, 2014 .

Parameter selection in Gaussian process interpolation: an empirical study of selection criteria

E. Vázquez, J. Bect, Paul Feliot, 2022 .

Model parameters in Gaussian process interpolation: an empirical study of selection criteria MODEL PARAMETERS IN GAUSSIAN PROCESS INTERPOLATION

E. Vázquez, J. Bect, Paul Feliot, 2022 .

Parameter selection in Gaussian process interpolation: an empirical study of selection criteria

E. Vázquez, J. Bect, Paul Feliot, 2021, 2107.06006.

A Bayesian approach to constrained single- and multi-objective optimization

E. Vázquez, J. Bect, Paul Feliot, 2016, Journal of Global Optimization.

Bayesian sequential design of computer experiments to estimate reliable sets

E. Vázquez, J. Bect, V. Chabridon, 2022 .

Robust Gaussian Process-Based Global Optimization Using a Fully Bayesian Expected Improvement Criterion

Julien Bect, Emmanuel Vázquez, Romain Benassi, 2011, LION.

Sequential Design of Multi-Fidelity Computer Experiments: Maximizing the Rate of Stepwise Uncertainty Reduction

E. Vázquez, J. Bect, N. Fischer, 2020, Technometrics.

User Preferences in Bayesian Multi-objective Optimization: The Expected Weighted Hypervolume Improvement Criterion

Julien Bect, Emmanuel Vázquez, Paul Feliot, 2018, LOD.

A Bayesian approach to constrained single- and multi-objective optimization

Julien Bect, Emmanuel Vázquez, Paul Feliot, 2015, Journal of Global Optimization.

Sequential design of computer experiments for the estimation of a probability of failure

Ling Li, Victor Picheny, David Ginsbourger, 2010, Statistics and Computing.

A Bayesian Approach to Constrained Multi-objective Optimization

Julien Bect, Emmanuel Vázquez, Paul Feliot, 2015, LION.

Bayesian Subset Simulation

Ling Li, Julien Bect, Emmanuel Vazquez, 2016, SIAM/ASA J. Uncertain. Quantification.

Bayesian Subset Simulation: a kriging-based subset simulation algorithm for the estimation of small probabilities of failure

Ling Li, Julien Bect, Emmanuel Vazquez, 2012, 1207.1963.

A numerical comparison of two sequential kriging-based algorithms to estimate a probability of failure

Ling Li, Julien Bect, Emmanuel Vazquez, 2010 .

Integrating hyper-parameter uncertainties in a multi-fidelity Bayesian model for the estimation of a probability of failure

Nicolas Fischer, Julien Bect, R'emi Stroh, 2017, Series on Advances in Mathematics for Applied Sciences.

Sequential design of experiments to estimate a probability of exceeding a threshold in a multi-fidelity stochastic simulator

Julien Bect, R'emi Stroh, S'everine Demeyer, 2017, 1707.08384.

BMOO: a Bayesian Multi-Objective Optimization algorithm

Julien Bect, Emmanuel Vazquez, Paul Feliot, 2016 .

A sequential Bayesian algorithm to estimate a probability of failure

Julien Bect, Emmanuel Vazquez, E. Vázquez, 2009 .

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

David Ginsbourger, Julien Bect, Ilya Molchanov, 2013 .

Adaptive Design of Experiments for Conservative Estimation of Excursion Sets

David Ginsbourger, Yann Richet, Julien Bect, 2016, Technometrics.

Fast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set

Victor Picheny, David Ginsbourger, Yann Richet, 2014, Technometrics.

Quantifying Uncertainties on Excursion Sets Under a Gaussian Random Field Prior

David Ginsbourger, Julien Bect, Dario Azzimonti, 2015, SIAM/ASA J. Uncertain. Quantification.

Fast kriging-based stepwise uncertainty reduction with application to the identification of an excursion set

Victor Picheny, David Ginsbourger, Julien Bect, 2019 .

Sequential search based on kriging: convergence analysis of some algorithms pdf

Julien Bect, Emmanuel Vázquez, E. Vázquez, 2011, ArXiv.

Towards new cross-validation-based estimators for Gaussian process regression: efficient adjoint computation of gradients

E. Vázquez, J. Bect, Paul Feliot, 2020, 2002.11543.

Pointwise consistency of the kriging predictor with known mean and covariance functions

Julien Bect, Emmanuel Vazquez, E. Vázquez, 2009, 0912.1479.

On the Quantification of Discretization Uncertainty: Comparison of Two Paradigms

Julien Bect, Emmanuel Vazquez, Souleymane Zio, 2021, 14th WCCM-ECCOMAS Congress.

Relabeling and Summarizing Posterior Distributions in Signal Decomposition Problems When the Number of Components is Unknown

Julien Bect, Gilles Fleury, Alireza Roodaki, 2013, IEEE Transactions on Signal Processing.

Summarizing posterior distributions in signal decomposition problems when the number of components is unknown

G. Fleury, A. Roodaki, J. Bect, 2011, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Generalized Fokker-Planck equation for piecewise-diffusion processes with boundary hitting resets

Julien Bect, Gilles Fleury, Hana Baili, 2006 .

An empirical Bayes approach for joint Bayesian model selection and estimation of sinusoids via reversible jump MCMC

Julien Bect, Gilles Fleury, Alireza Roodaki, 2010, 2010 18th European Signal Processing Conference.

On the joint Bayesian model selection and estimation of sinusoids via Reversible Jump MCMC in low SNR situations

Julien Bect, Gilles Fleury, Alireza Roodaki, 2010, 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010).

Bayesian sequential design of computer experiments for quantile set inversion

E. Vázquez, J. Bect, V. Chabridon, 2022, 2211.01008.

Bayesian multi-objective optimization for stochastic simulators: an extension of the Pareto Active Learning method

E. Vázquez, J. Bect, H. Baraffe, 2022, 2207.03842.

Parameter Selection in Gaussian Process Interpolation: An Empirical Study of Selection Criteria

E. Vázquez, J. Bect, Paul Feliot, 2021, SIAM/ASA J. Uncertain. Quantification.

Numerical Issues in Maximum Likelihood Parameter Estimation for Gaussian Process Interpolation

E. Vázquez, J. Bect, S. Petit, 2021, LOD.

Assessing fire safety using complex numerical models with a Bayesian multi-fidelity approach

Julien Bect, Séverine Demeyer, Nicolas Fischer, 2017 .

Bayesian Optimization Using Sequential Monte Carlo

E. Vázquez, J. Bect, R. Benassi, 2011, LION.

Numerical issues in maximum likelihood parameter estimation for Gaussian process regression

Julien Bect, Emmanuel Vazquez, Subhasish Basak, 2021, ArXiv.

Line of Sight controller tuning using Bayesian optimization of a high-level optronic criterion

Guillaume Sandou, Julien Bect, Gilles Duc, 2015 .

Gaussian process interpolation: the choice of the family of models is more important than that of the selection criterion

Julien Bect, Emmanuel Vazquez, Paul Feliot, 2021 .