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Bayesian Projected Calibration of Computer Models
v1v2 (latest)

Bayesian Projected Calibration of Computer Models

3 March 2018
Fangzheng Xie
Yanxun Xu
ArXiv (abs)PDFHTML

Papers citing "Bayesian Projected Calibration of Computer Models"

9 / 9 papers shown
Title
Gaussian Processes Sampling with Sparse Grids under Additive Schwarz
  Preconditioner
Gaussian Processes Sampling with Sparse Grids under Additive Schwarz Preconditioner
Haoyuan Chen
Rui Tuo
67
0
0
01 Aug 2024
Sobolev Calibration of Imperfect Computer Models
Sobolev Calibration of Imperfect Computer Models
Qingwen Zhang
Wenjia Wang
18
0
0
31 Mar 2024
Exploring Model Misspecification in Statistical Finite Elements via
  Shallow Water Equations
Exploring Model Misspecification in Statistical Finite Elements via Shallow Water Equations
Connor Duffin
P. Branson
M. Rayson
Mark Girolami
E. Cripps
T. Stemler
13
0
0
11 Jul 2023
Physical Parameter Calibration
Yang Li
Shifeng Xiong
40
0
0
30 Jul 2022
Data-driven discovery of interpretable causal relations for deep
  learning material laws with uncertainty propagation
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation
Xiao Sun
B. Bahmani
Nikolaos N. Vlassis
WaiChing Sun
Yanxun Xu
CMLAI4CE
116
26
0
20 May 2021
A Fast and Calibrated Computer Model Emulator: An Empirical Bayes
  Approach
A Fast and Calibrated Computer Model Emulator: An Empirical Bayes Approach
Vojtech Kejzlar
Mookyong Son
Shrijita Bhattacharya
T. Maiti
28
6
0
11 Aug 2020
Use of Machine Learning for unraveling hidden correlations between
  Particle Size Distributions and the Mechanical Behavior of Granular Materials
Use of Machine Learning for unraveling hidden correlations between Particle Size Distributions and the Mechanical Behavior of Granular Materials
I. Tejada
P. Antolin
AI4CE
37
13
0
10 Jun 2020
Variational Inference with Vine Copulas: An efficient Approach for
  Bayesian Computer Model Calibration
Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model Calibration
Vojtech Kejzlar
T. Maiti
56
6
0
28 Mar 2020
A theoretical framework of the scaled Gaussian stochastic process in
  prediction and calibration
A theoretical framework of the scaled Gaussian stochastic process in prediction and calibration
Mengyang Gu
Fangzheng Xie
Long Wang
47
11
0
10 Jul 2018
1