References in zbMATH (referenced in 44 articles , 1 standard article )

Showing results 1 to 20 of 44.
Sorted by year (citations)

1 2 3 next

  1. Mickaël Binois and Victor Picheny: GPareto: An R Package for Gaussian-Process-Based Multi-Objective Optimization and Analysis (2019) not zbMATH
  2. Picheny, Victor; Binois, Mickael; Habbal, Abderrahmane: A Bayesian optimization approach to find Nash equilibria (2019)
  3. Erickson, Collin B.; Ankenman, Bruce E.; Sanchez, Susan M.: Comparison of Gaussian process modeling software (2018)
  4. Gu, Mengyang; Wang, Long: Scaled Gaussian stochastic process for computer model calibration and prediction (2018)
  5. Gu, Mengyang; Wang, Xiaojing; Berger, James O.: Robust Gaussian stochastic process emulation (2018)
  6. Ludkovski, Mike; Risk, Jimmy; Zail, Howard: Gaussian process models for mortality rates and improvement factors (2018)
  7. Marmin, Sébastien; Ginsbourger, David; Baccou, Jean; Liandrat, Jacques: Warped Gaussian processes and derivative-based sequential designs for functions with heterogeneous variations (2018)
  8. Mathieu Carmassi; Pierre Barbillon; Matthieu Chiodetti; Merlin Keller; Eric Parent: CaliCo: a R package for Bayesian calibration (2018) arXiv
  9. Risk, Jimmy; Ludkovski, Michael: Sequential design and spatial modeling for portfolio tail risk measurement (2018)
  10. Rullière, Didier; Durrande, Nicolas; Bachoc, François; Chevalier, Clément: Nested kriging predictions for datasets with a large number of observations (2018)
  11. Ben Salem, Malek; Roustant, Olivier; Gamboa, Fabrice; Tomaso, Lionel: Universal prediction distribution for surrogate models (2017)
  12. Bernd Bischl, Jakob Richter, Jakob Bossek, Daniel Horn, Janek Thomas, Michel Lang: mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions (2017) arXiv
  13. Hu, Ruimeng; Ludkovsk, Mike: Sequential design for ranking response surfaces (2017)
  14. Maatouk, Hassan; Bay, Xavier: Gaussian process emulators for computer experiments with inequality constraints (2017)
  15. Muehlenstaedt, Thomas; Fruth, Jana; Roustant, Olivier: Computer experiments with functional inputs and scalar outputs by a norm-based approach (2017)
  16. Owen, N. E.; Challenor, P.; Menon, P. P.; Bennani, S.: Comparison of surrogate-based uncertainty quantification methods for computationally expensive simulators (2017)
  17. Amaran, Satyajith; Sahinidis, Nikolaos V.; Sharda, Bikram; Bury, Scott J.: Simulation optimization: a review of algorithms and applications (2016)
  18. Azzimonti, Dario; Bect, Julien; Chevalier, Clément; Ginsbourger, David: Quantifying uncertainties on excursion sets under a Gaussian random field prior (2016)
  19. Beck, Joakim; Guillas, Serge: Sequential design with mutual information for computer experiments (MICE): emulation of a tsunami model (2016)
  20. Bouhlel, Mohamed Amine; Bartoli, Nathalie; Otsmane, Abdelkader; Morlier, Joseph: An improved approach for estimating the hyperparameters of the Kriging model for high-dimensional problems through the partial least squares method (2016)

1 2 3 next