M. J. Bayarri, J. O. Berger, J. Cafeo, G. Garcia-donato, F. Liu et al., Computer model validation with functional output. The Annals of Statistics, pp.1874-1906, 2007.
DOI : 10.1214/009053607000000163
URL : http://doi.org/10.1214/009053607000000163

M. J. Bayarri, J. O. Berger, M. C. Kennedy, A. Kottas, R. Paulo et al., Predicting Vehicle Crashworthiness: Validation of Computer Models for Functional and Hierarchical Data, Journal of the American Statistical Association, vol.104, issue.487, pp.929-943, 2009.
DOI : 10.1198/jasa.2009.ap06623

M. J. Bayarri, V. D. Oliveira, and B. Sanso, Objective bayesian analysis of spatially correlated data, Journal of the American Statistical Association, vol.96, issue.456, pp.1361-1374, 2007.

J. Bect, D. Ginsbourger, L. Li, V. Picheny, and E. Vasquez, Sequential design of computer experiments for the estimation of a probability of failure, Statistics and Computing, vol.34, issue.4, 2012.
DOI : 10.2307/1269548
URL : https://hal.archives-ouvertes.fr/hal-00689580

L. M. Berliner, Monte carlo based ensemble forecasting, Statistics and Computing, vol.11, 2001.

K. Campbell, M. D. Mckay, and B. J. Williams, Sensitivity analysis when model outputs are functions, Reliability Engineering & System Safety, vol.91, issue.10-11, pp.911468-1472, 2006.
DOI : 10.1016/j.ress.2005.11.049

C. Chevalier, J. Bect, D. Ginsburger, E. Vasquez, V. Picheny et al., Fast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set, Technometrics, vol.13, issue.4, pp.455-465, 2014.
DOI : 10.1007/3-540-50871-6
URL : https://hal.archives-ouvertes.fr/hal-00641108

S. Conti and A. O. Hagan, Bayesian emulation of complex multi-output and dynamic computer models, Journal of Statistical Planning and Inference, vol.140, issue.3, pp.640-651, 2010.
DOI : 10.1016/j.jspi.2009.08.006

K. T. Fang, R. Li, and A. Sudjianto, Design and modeling for computer experiments, Computer Science and Data Analysis Series, vol.8, 2006.
DOI : 10.1201/9781420034899

K. T. Fang and D. K. Lin, Ch. 4. Uniform experimental designs and their applications in industry, Handbook of Statistics, vol.22, pp.131-178, 2003.
DOI : 10.1016/S0169-7161(03)22006-X
URL : https://hal.archives-ouvertes.fr/hal-01541536

T. E. Fricker, J. E. Oakley, and N. M. Urban, Multivariate Gaussian Process Emulators With Nonseparable Covariance Structures, Technometrics, vol.69, issue.1, pp.47-56, 2013.
DOI : 10.1007/978-3-662-03098-1

D. Higdon, J. Gattiker, B. Williams, and M. Rightley, Computer Model Calibration Using High-Dimensional Output, Journal of the American Statistical Association, vol.103, issue.482, pp.570-583, 2008.
DOI : 10.1198/016214507000000888
URL : http://www.stat.duke.edu/~fei/samsi/Readings/DHigdon/nedd4.pdf

Y. Hung, V. Joseph, and S. N. Melkote, Analysis of Computer Experiments With Functional Response, Technometrics, vol.39, issue.1, pp.35-44, 2015.
DOI : 10.1214/aos/1176346060
URL : http://arxiv.org/pdf/1211.1592

D. Jones, M. Schonlau, and W. Welch, Efficient global optimization of expensive black-box functions, Journal of Global Optimization, vol.13, issue.4, pp.455-492, 1998.
DOI : 10.1023/A:1008306431147

J. P. Kaipio and E. Somersalo, Statistics and Computational Inverse Problems, 2004.

M. C. Kennedy and A. O. Hagan, Bayesian calibration of computer models, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.3, pp.425-464, 2001.
DOI : 10.1111/1467-9868.00294
URL : http://onlinelibrary.wiley.com/doi/10.1111/1467-9868.00294/pdf

J. M. Marin and C. P. Robert, Bayesian core, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00450489

G. Perrin and C. Cannamela, A repulsion-based method for the definition and the enrichment of opotimized space filling designs in constrained input spaces, Journal de la Société Française de Statistique, vol.158, issue.1, pp.37-67, 2017.

G. Perrin, C. Soize, D. Duhamel, and C. Funfschilling, Identification of Polynomial Chaos Representations in High Dimension from a Set of Realizations, SIAM Journal on Scientific Computing, vol.34, issue.6, pp.2917-2945, 2012.
DOI : 10.1137/11084950X
URL : https://hal.archives-ouvertes.fr/hal-00770006

G. Perrin, C. Soize, and N. Ouhbi, Data-driven kernel representations for sampling with an unknown block dependence structure under correlation constraints, Computational Statistics & Data Analysis, vol.119, pp.139-154, 2018.
DOI : 10.1016/j.csda.2017.10.005
URL : https://hal.archives-ouvertes.fr/hal-01634877

M. T. Pratola, S. R. Sain, D. Bingham, M. Wiltberger, and E. J. Rigler, Fast Sequential Computer Model Calibration of Large Nonstationary Spatial-Temporal Processes, Technometrics, vol.99, issue.2, pp.232-242, 2013.
DOI : 10.1198/016214504000000241

P. Ranjan, M. Thomas, H. Teismann, and S. Mukhoti, Inverse Problem for a Time-Series Valued Computer Simulator via Scalarization, Open Journal of Statistics, vol.06, issue.03, pp.528-544, 2016.
DOI : 10.4236/ojs.2016.63045
URL : http://www.scirp.org/journal/PaperDownload.aspx?paperID=67748

J. Rougier, Efficient Emulators for Multivariate Deterministic Functions, Journal of Computational and Graphical Statistics, vol.17, issue.4, pp.827-843, 2008.
DOI : 10.1198/106186008X384032

R. T. Rubinstein and D. P. Kroese, Simulation and the Monte Carlo method, 2008.

J. Sacks, W. Welch, T. Mitchell, and H. Wynn, Design and Analysis of Computer Experiments, Statistical Science, vol.4, issue.4, pp.409-435, 1989.
DOI : 10.1214/ss/1177012413

T. J. Santner, B. J. Williams, and W. I. Notz, The design and analysis of computer experiments, 2003.
DOI : 10.1007/978-1-4757-3799-8

B. Williams, D. Higdon, J. Gattiker, L. Moore, M. Mckay et al., Combining experimental data and computer simulations, with an application to flyer plate experiments, Bayesian Analysis, vol.1, issue.4, pp.765-792, 2006.
DOI : 10.1214/06-BA125
URL : http://doi.org/10.1214/06-ba125