Preprints
- J. Demange-Chryst, F. Bachoc and J. Morio
"Shapley effect estimation in reliability-oriented sensitivity analysis with correlated inputs by importance sampling"
[arXiv]
- J. Bona-Pellissier, F. Bachoc and F. Malgouyres
"Parameter identifiability of a deep feedforward ReLU neural network"
[arXiv]
- F. Bachoc and A. Lagnoux
"Posterior contraction rates for constrained deep Gaussian processes in density estimation and classication"
[arXiv]
- F. Bachoc and M. Fathi
"Bounds in L1 Wasserstein distance on the normal approximation of general M-estimators"
[arXiv]
- C. Muehlmann, F. Bachoc, K. Nordhausen and M. Yi
"Test of the latent dimension of a spatial blind source separation model"
[arXiv]
- J. Bétancourt, F. Bachoc and T. Klein
"Gaussian process regression for scalar and functional inputs with funGp - the in-depth tour"
[hal]
- F. Bachoc, F. Gamboa, M. Halford, J-M. Loubes and L. Risser
"Entropic variable projection for explainability and intepretability"
[arXiv]
Refereed journal articles
- F. Bachoc, A. F. López-Lopera and O. Roustant
"Sequential construction and dimension reduction of Gaussian processes under inequality constraints"
SIAM Journal on Mathematics of Data Science, forthcoming
[arXiv]
- F. Bachoc, A. P. Peron and E. Porcu
"Multivariate Gaussian random fields over generalized product spaces involving the hypertorus"
Theory of Probability and Mathematical Statistics, special issue Theory and Applications of Random Fields, forthcoming
[hal]
- M.T. Vu, F. Bachoc and E. Pauwels
"Rate of convergence for geometric inference based on the empirical Christoffel function"
ESAIM: probability and statistics, forthcoming
[arXiv]
- C. Muehlmann, F. Bachoc and K. Nordhausen
"Blind source separation for non-stationary random fields"
Spatial Statistics, forthcoming
[arXiv]
- B. Broto, F. Bachoc, L. Clouvel and J-M Martinez
"Block-diagonal covariance estimation and application to the Shapley effects in sensitivity analysis"
SIAM/ASA Journal on uncertainty quantification, forthcoming
[arXiv]
- F. Bachoc, N. Durrande, D. Rullière and C. Chevalier
"Properties and comparison of some Kriging sub-model aggregation methods"
Mathematical geosciences, forthcoming
[pdf]
[hal]
[arXiv]
- D. Idier, A. Aurouet, F. Bachoc, A. Baills, J. Betancourt, F. Gamboa, T. Klein, A. F. López-Lopera, R. Pedreros, J. Rohmer and A. Thibault
"A user-oriented local coastal flooding early warning system using metamodelling techniques"
Journal of marine science and engineering, 9(11) (2021)
[journal]
- A. F. López-Lopera, D. Idier, J. Rohmer and F. Bachoc
"Multi-output Gaussian processes with functional data: a study on coastal flood hazard assessment"
Reliability engineering and system safety, forthcoming
[arXiv]
- F. Bachoc, E. Porcu, M. Bevilacqua, R. Furrer and T. Faouzi
"Asymptotically equivalent prediction in multivariate geostatistics"
Bernoulli, forthcoming
[arXiv]
- B. Broto, F. Bachoc, M. Depecker and J.M. Martinez
"Gaussian linear approximation for the estimation of the Shapley effects"
SIAM/ASA Journal on uncertainty quantification, forthcoming
[hal]
- F. Bachoc, T. Barthe, T. Santner and Y. Richet
"Sequential design of mixture experiments with an empirically determined input domain and an application to burn-up credit penalization of nuclear fuel rods"
Nuclear engineering and design, 374 (2021) 111034
[arXiv]
- A. Fradi, C. Samir and F. Bachoc
"A scalable approximate Bayesian inference for high-dimensional Gaussian processes"
Communications in statistics - theory and methods, (2020)
[journal]
- A. Fradi, Y. Feunteunp, C. Samir, M. Baklouti, F. Bachoc and J-M. Loubes
"Bayesian regression and classification using Gaussian process priors indexed by probability density functions"
Information sciences, 548(16) (2021) 56-68
[journal]
- J-M. Azais, F. Bachoc, A. Lagnoux and T.M.N. Nguyen
"Semi-parametric estimation of the variogram of a Gaussian process with stationary increments"
ESAIM: probability and statistics, 24 (2020) 842-882
[arXiv]
- F. Bachoc, A. Suvorikova, D. Ginsbourger, J-M. Loubes and V. Spokoiny
"Gaussian processes with multidimensional distribution inputs via optimal transport and Hilbertian embedding"
Electronic journal of statistics, 14(2) (2020) 2742-2772
[arXiv]
- F. Bachoc, J. Bétancourt, R. Furrer and T. Klein
"Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes"
Electronic journal of statistics, 14(1) (2020) 1962-2008
[arXiv]
- B. Broto, F. Bachoc and M. Depecker
"Variance reduction for estimation of Shapley effects and adaptation to unknown input distribution"
SIAM/ASA Journal on uncertainty quantification, 8(2) (2020) 693-716
[arXiv]
- F. Bachoc and A. Lagnoux
"Fixed-domain asymptotic properties of composite likelihood estimators for Gaussian processes"
Journal of statistical planning and inference, 209 (2020) 62-75
[hal]
- F. Bachoc, C. Helbert and V. Picheny
"Gaussian process optimization with failures: classification and convergence proof"
Journal of global optimization, 78 (2020) 483-506
[pdf]
[hal]
- J. Betancourt, F. Bachoc, T. Klein, D. Idier, R. Pedreros and J. Rohmer
"Gaussian process metamodeling of functional-input code for coastal flood hazard assessment"
Reliability engineering and system safety, 198 (2020) 106870
[hal]
- F. Bachoc, M. G. Genton, K. Nordhausen, A. Ruiz-Gazen and J. Virta
"Spatial blind source separation"
Biometrika, 107(3) (2020) 627-646
[arXiv]
- F. Bachoc, B. Broto, F. Gamboa and J-M. Loubes
"Gaussian processes indexed on the symmetric group: prediction and learning"
Electronic journal of statistics, 14 (2020) 503-546
[arXiv]
- F. Bachoc, D. Preinerstorfer and L. Steinberger
"Uniformly valid confidence intervals post-model-selection"
Annals of statistics, 48(1) (2020) 440-463.
[arXiv]
- F. Bachoc, A. Lagnoux and A. F. López-Lopera
"Maximum likelihood estimation for Gaussian processes under inequality constraints"
Electronic journal of statistics, 13(2) (2019) 2921-2969
[arXiv]
- F. Bachoc, M. Bevilacqua and D. Velandia
"Composite likelihood estimation for a Gaussian process under fixed domain asymptotics"
Journal of multivariate analysis, 174 (2019)
[arXiv]
- M. Ben Salem, F. Bachoc, O. Roustant, F. Gamboa and L. Tomaso
"Gaussian process based dimension reduction for goal-oriented sequential design"
SIAM/ASA Journal on uncertainty quantification, 7(4) (2019) 1369-1397
[hal]
- B. Broto, F. Bachoc, M. Depecker and J.M. Martinez
"Sensitivity indices for independent groups of variables"
Mathematics and computers in simulation, 163 (2019) 19-31
[arXiv]
- J. Bect, F. Bachoc and D. Ginsbourger
"A supermartingale approach to Gaussian process based sequential design of experiments"
Bernoulli, 25(4A) (2019) 2883-2919
[hal]
[arXiv]
- F. Bachoc, H. Leeb and B. Pötscher
"Valid confidence intervals for post-model-selection predictors"
Annals of statistics, 47(3) (2019) 1475-1504
[arXiv]
- F. Bachoc, G. Blanchard and P. Neuvial
"On the Post Selection Inference constant under Restricted Isometry Properties"
Electronic journal of statistics, 12(2) (2018) 3736-3757
[arXiv]
- A. F. López-Lopera, F. Bachoc, N. Durrande and O. Roustant
"Finite-dimensional Gaussian approximation with linear inequality constraints"
SIAM/ASA Journal on uncertainty quantification, 6(3) (2018) 1224-1255.
[pdf]
[arXiv]
- F. Bachoc, F. Gamboa, J-M. Loubes and N. Venet
"Gaussian process regression model for distribution inputs"
IEEE transactions on information theory, 64(10) (2018) 6620-6637
[pdf]
[arXiv]
- F. Bachoc
"Asymptotic analysis of covariance parameter estimation for Gaussian processes in the misspecified case"
Bernoulli 24(2) (2018) 1531-1575
[pdf]
[arXiv]
[supplementary material]
- D. Rullière, N. Durrande, F. Bachoc and C. Chevalier,
"Nested Kriging predictions for datasets with large number of observations",
Statistics and computing 28(4) (2018) 849-867
[pdf],
[hal]
[arXiv]
- F. Bachoc, A. Lagnoux and T.M.N. Nguyen,
"Cross-validation estimation of covariance parameters under fixed-domain asymptotics",
Journal of multivariate analysis 160 (2017) 42-67
[pdf]
[hal]
[arXiv]
- D. Velandia, F. Bachoc, M. Bevilacqua, X. Gendre, J-M. Loubes
"Maximum likelihood estimation for a bivariate Gaussian process under fixed domain asymptotics",
Electronic journal of statistics 11(2) (2017) 2978-3007
[pdf]
[arXiv]
- F. Bachoc, M. Ehler and M.Gräf
"Optimal configurations of lines and a statistical application"
Advances in computational mathematics 43(1) (2017) 113-126
[pdf]
[arXiv]
- R. Furrer, F. Bachoc and J. Du
"Asymptotic properties of multivariate tapering for estimation and prediction"
Journal of multivariate analysis 149 (2016) 177-191
[pdf]
[arXiv]
- F. Bachoc and Reinhard Furrer
"On the smallest eigenvalues of covariance matrices of multivariate spatial processes"
Stat 5 (2016) 102–107
[pdf]
[arXiv]
- F. Bachoc, K. Ammar and J.M. Martinez
"Improvement of code behaviour in a design of experiments by metamodeling"
Nuclear science and engineering 183(3) (2016) 387-406
[pdf]
[arXiv]
-
F. Bachoc
"Asymptotic analysis of the role of spatial
sampling for covariance parameter estimation of Gaussian
processes"
Journal of multivariate analysis 125 (2014) 1–35
[pdf]
[arXiv]
[supplementary material]
- F. Bachoc, G. Bois, J. Garnier and J.M. Martinez
"Calibration and improved prediction of computer models by universal Kriging"
Nuclear science and engineering 176(1) (2014) 81-97
[pdf]
[arXiv]
- F. Bachoc
"Cross Validation and
Maximum Likelihood estimation of hyper-parameters of
Gaussian processes with model misspecification"
Computational statistics and data analysis 66 (2013) 55–69
[pdf]
[arXiv]
Refereed international conference proceedings
- F. Bachoc, T. Cesari and S. Gerchinovitz
"Instance-dependent bounds for zeroth-order Lipschitz optimization with error certificates"
NeurIPS, Conference on Neural Information Processing Systems, 2021
[arXiv]
- F. Bachoc, T. Cesari and S. Gerchinovitz
"The sample complexity of level set approximation"
AISTATS - oral presentation, International Conference on Artificial Intelligence and Statistics, 2021
[arXiv]
- D. Idier, A. Aurouet, F. Bachoc, A. Baills, J. Betancourt, J. Durand, R. Mouche, J. Rohmer, F. Gamboa, T. Klein, J. Lambert, G. Le
Cozannet, S. Le Roy, J. Louisor, R. Pedreros and A-L Véron
"Toward a user-based, robust and fast running method for
coastal flooding forecast, early warning, and risk prevention"
Journal of coastal research, special issue 95, p. 11-15, proceedings from the International Coastal Symposium (ICS) 2020, forthcoming
- C. Samir, J-M. Loubes, A.-F. Yao and F. Bachoc
"Learning a Gaussian process model on the Riemannian manifold of non-decreasing distribution functions"
PRICAI, Pacific Rim International Conference on Artificial Intelligence, Trends in Artificial Intelligence pp 107-120, 2019
[hal]
- A. F. López-Lopera, F. Bachoc, N. Durrande, J. Rohmer, D. Idier and O. Roustant
"Approximating Gaussian process emulators with linear inequality constraints and noisy observations via MC and MCMC"
MCQMC, Monte Carlo and Quasi-Monte Carlo Methods (2018)
[arXiv]
Refereed book chapters
- F. Bachoc
"Asymptotic analysis of maximum likelihood estimation of covariance parameters for Gaussian processes: an introduction with proofs"
Advances in Contemporary Statistics and Econometrics (2021) pp 283-303, Festschrift in honor of Christine Thomas Agnan
[arXiv]
- F. Bachoc, E. Contal, H. Maatouk and D. Rullière
"Gaussian processes for computer experiments"
ESAIM: Proceedings and Surveys 60 (2017) 163 - 179
[pdf]
- F. Bachoc, A. Bachouch and L. Lenôtre
"Hastings-Metropolis algorithm on Markov chains for small-probability estimation"
ESAIM: Proceedings and Surveys 48 (2015) p.276
[pdf]
[arXiv]
Refereed national conference proceedings
-
F. Bachoc, D. Preinerstorfer and L. Steinberger
"Uniformly valid confidence intervals post-model-selection"
Proceedings of the 49e Journées de
Statistique
Avignon, May 29-June 2 2017
[pdf]
-
F. Bachoc, F. Gamboa, J-M. Loubes and N. Venet
"Gaussian process regression model for distribution inputs"
Proceedings of the 49e Journées de
Statistique
Avignon, May 29-June 2 2017
[pdf]
-
F. Bachoc, H. Leeb and B. Pötscher
"Valid confidence intervals for post-model-selection predictors"
Proceedings of the 47e Journées de
Statistique
Lille, 1-5 June 2015
[pdf]
-
F. Bachoc, J. Garnier and J.M. Martinez
"Maximum de vraisemblance et
validation croisée pour l’estimation des hyper-paramètres de
covariance pour le Krigeage",
Proceedings of the 45e Journées de
Statistique Toulouse, 27-31 Mai 2013
[pdf]
Technical reports
-
J.M. Martinez, A. Marrel, N. Gilardi and F. Bachoc,
"Krigeage par processus gaussiens Librairie gpLib",
Internal report CEA DEN/DANS/DM2S/STMF/LGLS/RT/12-026/A. 50p. 2012
Available upon request
-
F. Bachoc, G. Bois and J.M. Martinez
"Contribution à la validation des codes de calcul par Processus Gaussiens.
Application à la calibration du modèle de frottement pariétal de Flica 4",
Internal report CEA DEN/DANS/DM2S/STMF/LGLS/RT/12-007/A. 42p. 2012
Available upon request
-
F. Bachoc
"Calibration de modèles physiques par méthodes probabilistes",
Internal report CEA DEN/DANS/DM2S/SFME/LGLS/RT/10-015/A. 78p. 2010
Available upon request
Software
-
J. Betancourt, F. Bachoc, T. Klein, D. Idier and J. Rohmer,
"funGp: Gaussian process models for scalar and functional inputs",
R package 2020
[link]