Related references
Note: Only part of the references are listed.An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis
Xiaobing Shang et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2023)
Machine learning approaches to estimate suspension parameters for performance degradation assessment using accurate dynamic simulations
Yongjun Pan et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2023)
Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges
Yanwen Xu et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2023)
Adaptive subset simulation for time-dependent small failure probability incorporating first failure time and single-loop surrogate model
Hongyuan Guo et al.
STRUCTURAL SAFETY (2023)
Efficient subset simulation for rare-event integrating point-evolution kernel density and adaptive polynomial chaos kriging
Hongyuan Guo et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)
Uncertainty propagation in risk and resilience analysis of hierarchical systems
Armin Tabandeh et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2022)
Mapping functions: A physics-guided, data-driven and algorithm-agnostic machine learning approach to discover causal and descriptive expressions of engineering phenomena
M. Z. Naser
MEASUREMENT (2021)
Probabilistic model updating via variational Bayesian inference and adaptive Gaussian process modeling
Pinghe Ni et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2021)
Structural Deterioration Modeling Using Variational Inference
Markus R. Dann et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2019)
Model selection for degradation modeling and prognosis with health monitoring data
Khanh T. P. Nguyen et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2018)
Variational Inference: A Review for Statisticians
David M. Blei et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2017)
A tutorial introduction to Bayesian inference for stochastic epidemic models using Approximate Bayesian Computation
Theodore Kypraios et al.
MATHEMATICAL BIOSCIENCES (2017)
LIF: A new Kriging based learning function and its application to structural reliability analysis
Zhili Sun et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2017)
Hessian-based adaptive sparse quadrature for infinite-dimensional Bayesian inverse problems
Peng Chen et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2017)
Bayesian approach to inverse problems for functions with a variable-index Besov prior
Junxiong Jia et al.
INVERSE PROBLEMS (2016)
A Variational Bayes Spatiotemporal Model for Electromagnetic Brain Mapping
F. S. Nathoo et al.
BIOMETRICS (2014)
NON-GAUSSIAN STATISTICAL INVERSE PROBLEMS. PART I: POSTERIOR DISTRIBUTIONS
Sari Lasanen
INVERSE PROBLEMS AND IMAGING (2012)
BESOV PRIORS FOR BAYESIAN INVERSE PROBLEMS
Masoumeh Dashti et al.
INVERSE PROBLEMS AND IMAGING (2012)
Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion
S. Oladyshkin et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2012)
APPROXIMATION OF BAYESIAN INVERSE PROBLEMS FOR PDES
S. L. Cotter et al.
SIAM JOURNAL ON NUMERICAL ANALYSIS (2010)
Aleatory or epistemic? Does it matter?
Armen Der Kiureghian et al.
STRUCTURAL SAFETY (2009)
Computer model calibration using high-dimensional output
Dave Higdon et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2008)
Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems
JC Helton et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2003)
Strong optimality of the normalized ML models as universal codes and information in data
J Rissanen
IEEE TRANSACTIONS ON INFORMATION THEORY (2001)
Model selection and the principle of minimum description length
MH Hansen et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2001)
Bayesian calibration of computer models
MC Kennedy et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2001)
Counting probability distributions: Differential geometry and model selection
IJ Myung et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2000)