References in zbMATH (referenced in 74 articles , 1 standard article )

Showing results 1 to 20 of 74.
Sorted by year (citations)

1 2 3 4 next

  1. Allaire, Frédéric; Mallet, Vivien; Filippi, Jean-Baptiste: Novel method for a posteriori uncertainty quantification in wildland fire spread simulation (2021)
  2. Balata, Alessandro; Ludkovski, Michael; Maheshwari, Aditya; Palczewski, Jan: Statistical learning for probability-constrained stochastic optimal control (2021)
  3. Evandro Konzen, Yafeng Cheng, Jian Qing Shi: Gaussian Process for Functional Data Analysis: The GPFDA Package for R (2021) arXiv
  4. Mastrippolito, Franck; Aubert, Stéphane; Ducros, Frédéric: Kriging metamodels-based multi-objective shape optimization applied to a multi-scale heat exchanger (2021)
  5. Rohrbeck, Christian; Simpson, Emma S.; Towe, Ross P.: A spatio-temporal model for Red Sea surface temperature anomalies (2021)
  6. Xiao, Qian; Xu, Hongquan: A mapping-based universal kriging model for order-of-addition experiments in drug combination studies (2021)
  7. Yang, Yang; Ji, Chunlin; Deng, Ke: Rapid design of metamaterials via multitarget Bayesian optimization (2021)
  8. Azaïs, Jean-Marc; Bachoc, François; Lagnoux, Agnès; Nguyen, Thi Mong Ngoc: Semi-parametric estimation of the variogram scale parameter of a Gaussian process with stationary increments (2020)
  9. Bachoc, François; Helbert, Céline; Picheny, Victor: Gaussian process optimization with failures: classification and convergence proof (2020)
  10. Binois, Mickaël; Ginsbourger, David; Roustant, Olivier: On the choice of the low-dimensional domain for global optimization via random embeddings (2020)
  11. El Amri, Mohamed Reda; Helbert, Céline; Lepreux, Olivier; Zuniga, Miguel Munoz; Prieur, Clémentine; Sinoquet, Delphine: Data-driven stochastic inversion via functional quantization (2020)
  12. Gahrooei, Mostafa Reisi; Yan, Hao; Paynabar, Kamran: Comments on: “On active learning methods for manifold data” (2020)
  13. Guan, Qian; Reich, Brian J.; Laber, Eric B.; Bandyopadhyay, Dipankar: Bayesian nonparametric policy search with application to periodontal recall intervals (2020)
  14. Hu, Ruimeng: Deep learning for ranking response surfaces with applications to optimal stopping problems (2020)
  15. López-Lopera, Andrés F.; Bachoc, François; Durrande, Nicolas; Rohmer, Jérémy; Idier, Déborah; Roustant, Olivier: Approximating Gaussian process emulators with linear inequality constraints and noisy observations via MC and MCMC (2020)
  16. Lu, Xuefei; Rudi, Alessandro; Borgonovo, Emanuele; Rosasco, Lorenzo: Faster Kriging: facing high-dimensional simulators (2020)
  17. Mike Ludkovski: mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms (2020) arXiv
  18. Valadão, Mônica A. C.; Batista, Lucas S.: A comparative study on surrogate models for SAEAs (2020)
  19. Wang, Jialei; Clark, Scott C.; Liu, Eric; Frazier, Peter I.: Parallel Bayesian global optimization of expensive functions (2020)
  20. Xie, Fangzheng; Xu, Yanxun: Adaptive Bayesian nonparametric regression using a kernel mixture of polynomials with application to partial linear models (2020)

1 2 3 4 next