Deep coregionalization for the emulation of simulation-based spatial-temporal fields

DOI10.1016/j.jcp.2020.109984OpenAlexW3106535526MaRDI QIDQ2128339

Shandian Zhe, Weiwei Xing, Robert M. Kirby

Publication date: 21 April 2022

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.07577

zbMATH Keywords

Gaussian processemulationsurrogate modelmultifidelity modelspatial-temporal field

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Fluid mechanics (76-XX)

Related Items (1)

A metalearning approach for physics-informed neural networks (PINNs): application to parameterized PDEs

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Multi-output separable Gaussian process: towards an efficient, fully Bayesian paradigm for uncertainty quantification
• Reduced-order models for parameter dependent geometries based on shape sensitivity analysis
• Bayesian emulation of complex multi-output and dynamic computer models
• Functional data analysis
• The design and analysis of computer experiments.
• Manifold learning for the emulation of spatial fields from computational models
• Machine learning of linear differential equations using Gaussian processes
• The heat equation and reflected Brownian motion in time-dependent domains.
• Physics-informed cokriging: a Gaussian-process-regression-based multifidelity method for data-model convergence
• Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
• Bayesian Calibration of Computer Models
• A Stochastic Collocation Algorithm with Multifidelity Models
• Kernels for Vector-Valued Functions: A Review
• Galerkin reduced-order modeling scheme for time-dependent randomly parametrized linear partial differential equations
• 10.1162/15324430260185646
• Computer Model Calibration Using High-Dimensional Output
• Uniformly distributed sequences with an additional uniform property
• Probabilistic Principal Component Analysis
• Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization
• Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling
• Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models
• Predicting the output from a complex computer code when fast approximations are available
• Advanced Lectures on Machine Learning
• Numerical Solution of the Navier-Stokes Equations
• Computational Fluid Dynamics

This page was built for publication: Deep coregionalization for the emulation of simulation-based spatial-temporal fields