ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2201.10745
  4. Cited By
Control Variate Polynomial Chaos: Optimal Fusion of Sampling and
  Surrogates for Multifidelity Uncertainty Quantification

Control Variate Polynomial Chaos: Optimal Fusion of Sampling and Surrogates for Multifidelity Uncertainty Quantification

26 January 2022
Hang Yang
Y. Fujii
K. W. Wang
Alex A. Gorodetsky
ArXivPDFHTML

Papers citing "Control Variate Polynomial Chaos: Optimal Fusion of Sampling and Surrogates for Multifidelity Uncertainty Quantification"

5 / 5 papers shown
Title
Grouped approximate control variate estimators
Grouped approximate control variate estimators
Alex A. Gorodetsky
J. Jakeman
M. Eldred
16
2
0
22 Feb 2024
Multilevel Surrogate-based Control Variates
Multilevel Surrogate-based Control Variates
M. R. E. Amri
Paul Mycek
S. Ricci
M. Lozzo
20
3
0
19 Jun 2023
Context-aware learning of hierarchies of low-fidelity models for
  multi-fidelity uncertainty quantification
Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification
Ionut-Gabriel Farcas
Benjamin Peherstorfer
T. Neckel
Frank Jenko
H. Bungartz
AI4CE
32
11
0
20 Nov 2022
Ensemble approximate control variate estimators: Applications to
  multi-fidelity importance sampling
Ensemble approximate control variate estimators: Applications to multi-fidelity importance sampling
Trung T. Pham
Alex A. Gorodetsky
34
14
0
07 Jan 2021
Recursive co-kriging model for Design of Computer experiments with
  multiple levels of fidelity with an application to hydrodynamic
Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity with an application to hydrodynamic
Loic Le Gratiet
AI4CE
88
292
0
02 Oct 2012
1