Publications

Google scholar publication page (probably more up to date than below).

Below a list of papers, by topic:

Kernels methods and (Gaussian) random field modelling
Targeted experimental design / Random field-based set estimation methods
Bayesian optimization methods
Other topics and papers in application fields

Targeted experimental design / Random field-based set estimation methods

CRPS-Based Targeted Sequential Design with Application in Chemical Space.
Status: arXiv preprint arXiv:2503.11250, 2025.
Joint work with Lea Friedli*, Athénaïs Gautier, and Anna Broccard.
Consistency of some sequential experimental design strategies for excursion set estimation based on vector-valued Gaussian processes.
Status: In Electronic Journal of Statistics 18 (2), 5091-5131, 2024. [preprint]
Joint work with Philip Stange*.

Uncertainty Quantification and Experimental Design for large-scale linear Inverse Problems under Gaussian Process Priors.
Status: In SIAM/ASA Journal on Uncertainty Quantification, 11(1), 168-198, 2023. [preprint]
Joint work with Cédric Travelletti* and Niklas Linde.

Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling.
Status: In Annals of Applied Statistics, 15(2): 597-618, 2021. [preprint]
Joint work with Trygve Olaf Fossum*, Cédric Travelletti, Jo Eidsvik, and Kanna Rajan.

Adaptive Design of Experiments for Conservative Estimation of Excursion Sets.
Status: In Technometrics, 63:1, 13-26, 2021. [preprint]
Joint work with Dario Azzimonti*, Julien Bect, Clement Chevalier, Yann Richet.

Conditions for the finiteness of the moments of the volume of level sets.
Status: In Electronic Communications in Probability, Volume 24 (2019), paper no. 17, 8 pp.
Joint work with Diego Armentano, Jean-Marc Azais*, José Rafael Leon.

A supermartingale approach to Gaussian process based sequential design of experiments.
Status: In Bernoulli 25(4A):2883-2919, 2019.
Joint work with Julien Bect* and François Bachoc.

Profile extrema for visualizing and quantifying uncertainties on excursion regions. Application to coastal flooding.
Status: Technometrics, 61:4, 474-493, 2019.
Joint work with Dario Azzimonti*, Jeremy Rohmer, Deborah Idier.

Estimating orthant probabilities of high dimensional Gaussian vectors with an application to set estimation.
Status: Journal of Computational and Graphical Statistics, 27(2):255-267, 2018. [preprint]
Joint work with Dario Azzimonti*

Quantifying uncertainties on excursion sets under a Gaussian random field prior.
Status: In SIAM/ASA J. Uncertainty Quantification, 4(1), 850–874, 2016. [preprint]
Joint work with Dario Azzimonti*, Julien Bect, and Clement Chevalier

Quantifying uncertainty on Pareto fronts with Gaussian Process conditional simulations.
Status: European Journal of Operational Research, 243(2), 386-394, 2015. [preprint]
Joint work with Mickael Binois*, and Olivier Roustant

Bayesian adaptive reconstruction of profile optima and optimizers.
Status: In SIAM/ASA J. Uncertainty Quantification, 2(1):490-510, 2014. [preprint]
Joint work with Jean Baccou, Clement Chevalier, Nicolas Garland, Yann Monerie, Frederic Perales

Fast kriging-based stepwise uncertainty reduction with application to the identification of an excursion set.
Status: Technometrics, 56(4):455-465, 2014. [preprint]
Joint work with Julien Bect, Clément Chevalier*, Victor Picheny, Yann Richet and Emmanuel Vazquez

The KrigInv package: An efficient and user-friendly R implementation of Kriging-based inversion algorithms.
Status: In Computational Statistics and Data Analysis 71, pp. 1021-1034, 2014. [preprint]
Joint work with Clément Chevalier* and Victor Picheny

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models.
Status: In mODa 10 - Advances in Model-Oriented Design and Analysis. Contributions to Statistics, pp 35-43, 2013. [preprint]
Joint work with Julien Bect, Clément Chevalier* and Ilya Molchanov

Sequential design of computer experiments for the estimation of a probability of failure.
Status: In Statistics and Computing, 22 (3): 773-793, 2012. [preprint]
Joint work with Julien Bect*, Ling Li, Victor Picheny, Yann Richet and Emmanuel Vazquez*

Adaptive Designs of experiments for accurate approximation of target regions.
Status: In Journal of Mechanical Design, 132 (7), 2010. [preprint]
Joint work with Rafi Haftka, Nam-Ho Kim, Victor Picheny* and Olivier Roustant

Kernel methods and (Gaussian) random field modelling

Continuous logistic Gaussian random measure fields for spatial distributional modelling.
Joint work with Athénaïs Gautier*

Efficient pooling of predictions via kernel embeddings.
Joint work with Sam Allen* and Johanna Ziegel

Fast Calculation of Gaussian Process Multiple-Fold Cross-Validation Residuals and their Covariances.
Status: In Journal of Computational and Graphical Statistics 34 (1), 1-14, 2025.
Joint work with Cedric Schärer

Disintegration of Gaussian Measures for Sequential Assimilation of Linear Operator Data.
Status: In Electronic Journal of Statistics 18 (2), 3825-3857, 2024. [preprint]
Joint work with Cédric Travelletti*

Characteristic kernels on Hilbert spaces, Banach spaces, and on sets of measures.
Status: Bernoulli 30 (2), 1441-1457, 2024. [preprint]
Joint work with Lutz Dümbgen and Johanna Ziegel*

Evaluating forecasts for high-impact events using transformed kernel scores.
Status: In SIAM/ASA Journal on Uncertainty Quantification 11 (3), 906 - 940.
Joint work with Sam Allen* and Johanna Ziegel

Gaussian processes with multidimensional distribution inputs via optimal transport and Hilbertian embedding.
Status: Electronic Journal of Statistics 14 (2), 2742-2772.
Joint work with François Bachoc*, Alexandra Suvorikova, Jean-Michel Loubes, Vladimir Spokoiny

Warped Gaussian processes and derivative-based sequential design for functions with heterogeneous variations.
Status: SIAM/ASA J. Uncertainty Quantification 6(3):991-1018, 2018. [Older preprint]
Joint work with Sebastien Marmin*, Jean Baccou and Jacques Liandrat.

On degeneracy and invariances of random fields paths with applications in Gaussian process modelling.
Status: Journal of Statistical Planning and Inference, 170, 117-128, 2016. [Older arxiv paper]
Joint work with Olivier Roustant and Nicolas Durrande

On ANOVA decompositions of kernels and Gaussian random field paths.
Status: In Monte Carlo and Quasi-Monte Carlo Methods. Springer Proceedings in Mathematics & Statistics vol 163, pp 315-330, 2016. [Arxiv preprint]
Joint work with Nicolas Durrande, Nicolas Lenz, Olivier Roustant and Dominic Schuhmacher

Fast Update of Conditional Simulation Ensembles.
Status: In Mathematical Geosciences, 47(7), 771-789, 2015. [preprint]
Joint work with Clement Chevalier and Xavier Emery

Kernels and designs for modelling invariant functions: From group invariance to additivity.
Status: In mODa 10 - Advances in Model-Oriented Design and Analysis. Contributions to Statistics 2013, pp 107-115. [preprint]
Joint work with Nicolas Durrande and Olivier Roustant

ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis.
Status: In Journal of Multivariate Analysis, 115, 57-67, 2013. [Older preprint]
Joint work with Laurent Carraro, Nicolas Durrande* and Olivier Roustant

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations.
Status: In SIAM/ASA J. Uncertainty Quantification, 1(1), 57-78, 2013. [preprint]
Joint work with Victor Picheny*

Argumentwise invariant kernels for the approximation of invariant functions.
Status: In Annales de la Faculté des Sciences de Toulouse, 21 (3): 501-527, 2012. [preprint]
Joint work with Xavier Bay, Laurent Carraro and Olivier Roustant

Additive covariance kernels for high-dimensional gaussian process modeling.
Status: In Annales de la Faculté des Sciences de Toulouse, 21 (3): 481-499, 2012. [preprint]
Joint work with Nicolas Durrande* and Olivier Roustant

Corrected Kriging update formulae for batch-sequential data assimilation.
Status: In Lecture Notes in Earth System Sciences 2014, pp 119-122 Joint work with Clément Chevalier* and Xavier Émery

DiceKriging, DiceOptim: Two R packages for the analysis of computer experiments by kriging-based metamodelling and optimization.
Status: In Journal of Statistical Software, 51 (1), 2012
Joint work with Yves Deville and Olivier Roustant*

A note on the choice and the estimation of Kriging models for the analysis of deterministic computer experiments.
Status: In Applied Stochastic Models for Business and Industry, 25 (2): 115-131, 2009. [preprint]
Joint work with Anca Badea, Laurent Carraro, Delphine Dupuy and Olivier Roustant

Bayesian optimization methods

Goal-oriented adaptive sampling under random field modelling of response probability distributions.
Status: In ESAIM: Proceedings and surveys 71 (FGS’2019), 89-100. [preprint]
Joint work with Athenais Gautier* and Guillaume Pirot

Kernels over sets of finite sets using RKHS embeddings, with application to Bayesian (combinatorial) optimization.
Status: In Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108, 2731-2741, 2020. [preprint]
Joint work with Poompol Buathong (joint*) and Tipaluck Krityakierne

On the choice of the low-dimensional domain for global optimization via random embeddings.
Status: Journal of Global Optimization, 76, 69-90, 2020. [preprint]
Joint work with Mickael Binois* and Olivier Roustant

Efficient batch-sequential Bayesian optimization with moments of truncated Gaussian vectors.
Joint work with Clément Chevalier and Sébastien Marmin*

Differentiating the multipoint Expected Improvement for optimal batch design.
Machine Learning, Optimization, and Big Data, Lecture Notes in Computer Science vol. 9432, pp 37-48, 2015. [preprint]
Joint work with Clément Chevalier and Sébastien Marmin*

Global optimization with sparse and local Gaussian process models.
Machine Learning, Optimization, and Big Data, Lecture Notes in Computer Science vol. 9432, pp 185-196, 2015.
Joint work with Tipaluck Krityakierne*

A warped kernel improving robustness in Bayesian optimization via random embeddings.
Learning and Intelligent Optimization, Lecture Notes in Computer Science vol. 8994, pp 281-286, 2015. [preprint]
Joint work with Mickael Binois* and Olivier Roustant

Noisy kriging-based optimization methods: a unified implementation within the DiceOptim package.
Status: In Computational Statistics and Data Analysis 71, pp. 1035-1053, 2014. [preprint]
Joint work with Victor Picheny*

Fast computation of the multipoint Expected Improvement with applications in batch selection.
Status: In Learning and Intelligent Optimization, Lecture Notes in Computer Science vol. 7997, pp 59-69, 2013. [Also presented as poster and short paper at NIPS 2012 Workshop on Bayesian Optimization and Decision Making] [preprint]
Joint work with Clément Chevalier*

Quantile-Based Optimization of Noisy Computer Experiments with Tunable Precision.
Status: In Technometrics, 55(1), 2013 [with discussion and rejoinder]. [preprint]
Joint work with Gregory Caplin, Victor Picheny* and Yann Richet

Benchmark of kriging-based infill criteria for noisy optimization.
Status: In Structural and Multidisciplinary Optimization 48(3), 607-626. [preprint]
Joint work with Victor Picheny* and Tobias Wagner

Parallel Budgeted Optimization Applied to the Design of an Air Duct.
Status: OMD2 Technical report, 2012.
Joint work with Ramunas Girdziusas*, Rodolphe Le Riche, Fabien Viale

Expected improvements for the asynchronous parallel global optimization of expensive functions : potentials and challenges.
Status: In Learning and Intelligent Optimization, Lecture Notes in Computer Science vol. 7219, pp 413-418, 2012. [preprint]
Joint work with Janis Janusevskis* and Rodolphe Le Riche

Dealing with asynchronicity in parallel Gaussian Process based global optimization.
Status: OMD2 Technical report, 2010.
Joint work with Janis Janusevskis and Rodolphe Le Riche

Towards Gaussian Process-based Optimization with Finite Time Horizon.
Status: In mODa 9 Advances in Model-Oriented Design and Analysis, pages 89-96, Physica-Verlag HD, Contributions to Statistics, 2010. [preprint]
Joint work with Rodolphe Le Riche

Noisy Expected Improvement and on-line computation time allocation for the optimization of simulators with tunable fidelity.
Status: In Proceedings of the 2nd International Conference on Engineering Optimization, 2010.
Joint work with Victor Picheny*

Kriging is well-suited to parallelize optimization.
Status: In Computational Intelligence in Expensive Optimization Problems, pages 131-162, Springer Berlin Heidelberg, Adaptation Learning and Optimization, 2010. [A previous (unpublished) version following up a talk presented at the NCP07 conference is available online. If you wish to refer to this work, please better refer to the 2010 (published) book chapter.]
Joint work with Laurent Carraro and Rodolphe Le Riche

Discrete mixtures of kernels for Kriging-based optimization.
Status: In Quality and Reliability Eng. Int., 24 (6): 681-691, 2008.
Joint work with Laurent Carraro and Céline Helbert [Older preprint]

Prof. Dr. David Ginsbourger

Publications

Targeted experimental design / Random field-based set estimation methods

Kernel methods and (Gaussian) random field modelling

Bayesian optimization methods

Other topics and papers in application fields