Clustered active-subspace based local Gaussian process emulator for high-dimensional and complex computer models
From MaRDI portal
Publication:2134712
DOI10.1016/j.jcp.2021.110840OpenAlexW3211498338MaRDI QIDQ2134712
Jinglai Li, Junda Xiong, Xin Cai
Publication date: 3 May 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2101.00057
Stochastic analysis (60Hxx) Nonparametric inference (62Gxx) Probabilistic methods, stochastic differential equations (65Cxx)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Multi-output local Gaussian process regression: applications to uncertainty quantification
- Constrained global optimization of expensive black box functions using radial basis functions
- Sequential design of computer experiments for the estimation of a probability of failure
- Gaussian processes with built-in dimensionality reduction: applications to high-dimensional uncertainty propagation
- A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification
- A survey of cross-validation procedures for model selection
- An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
- Data driven governing equations approximation using deep neural networks
- Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
- Gaussian process surrogates for failure detection: a Bayesian experimental design approach
- Active Subspaces
- Sliced Inverse Regression for Dimension Reduction
- Dimension Reduction for Gaussian Process Emulation: An Application to the Influence of Bathymetry on Tsunami Heights
- Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations
- Large-Scale PDE-Constrained Optimization: An Introduction
- The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
- Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach
- Adaptive Gaussian Process Approximation for Bayesian Inference with Expensive Likelihood Functions
- When Bifidelity Meets CoKriging: An Efficient Physics-Informed MultiFidelity Method
- Mercer Kernels and Integrated Variance Experimental Design: Connections Between Gaussian Process Regression and Polynomial Approximation
- Comment
- A radial basis function method for global optimization
This page was built for publication: Clustered active-subspace based local Gaussian process emulator for high-dimensional and complex computer models