Bayesian sensitivity analysis of a 1D vascular model with Gaussian process emulators.
Sign Up to like & getrecommendations! Published in 2017 at "International journal for numerical methods in biomedical engineering"
DOI: 10.1002/cnm.2882
Abstract: One-dimensional models of the cardiovascular system can capture the physics of pulse waves but involve many parameters. Since these may vary among individuals, patient-specific models are difficult to construct. Sensitivity analysis can be used to… read more here.
Keywords: analysis; sensitivity; model; sensitivity analysis ... See more keywords
Producing chemically accurate atomic Gaussian process regression models by active learning for molecular simulation
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Computational Chemistry"
DOI: 10.1002/jcc.27006
Abstract: Machine learning is becoming increasingly more important in the field of force field development. Never has it been more vital to have chemically accurate machine learning potentials because force fields become more sophisticated and their… read more here.
Keywords: active learning; regression models; chemically accurate; gaussian process ... See more keywords
Adaptive regularized Gaussian process regression for application in the context of hydrogen adsorption on graphene sheets
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Computational Chemistry"
DOI: 10.1002/jcc.27035
Abstract: We present a Gaussian process regression (GPR) scheme with an adaptive regularization scheme applied to the QM7 and QM9 test set, several protonated water clusters and specifically to the problem of atomic hydrogen adsorption on… read more here.
Keywords: adsorption graphene; hydrogen adsorption; graphene sheets; gaussian process ... See more keywords
Referenceless magnetic resonance temperature imaging using Gaussian process modeling
Sign Up to like & getrecommendations! Published in 2017 at "Medical Physics"
DOI: 10.1002/mp.12231
Abstract: Purpose During magnetic resonance (MR)‐guided thermal therapies, water proton resonance frequency shift (PRFS)‐based MR temperature imaging can quantitatively monitor tissue temperature changes. It is widely known that the PRFS technique is easily perturbed by tissue… read more here.
Keywords: phase; temperature; magnetic resonance; temperature imaging ... See more keywords
Evaluation of Matrix Effects in SIMS Using Gaussian Process Regression: The Case of Olivine Mg Isotope Microanalysis
Sign Up to like & getrecommendations! Published in 2025 at "Rapid Communications in Mass Spectrometry"
DOI: 10.1002/rcm.10038
Abstract: Matrix effects by secondary ion mass spectrometry (SIMS) are empirically corrected by calibration using matrix‐matched reference materials. However, conventional parametric regression cannot estimate the prediction uncertainty to account for the difference in compositions of new… read more here.
Keywords: gaussian process; regression; matrix effects; process regression ... See more keywords
Data‐based nonlinear learning control for aircraft trajectory tracking via Gaussian process regression
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Robust and Nonlinear Control"
DOI: 10.1002/rnc.7526
Abstract: In this article, a new data‐based iterative learning control (ILC) algorithm is proposed via Gaussian process regression (GPR) to accomplish the trajectory tracking objective of aircraft subject to completely unknown dynamics and strong nonlinearities. The… read more here.
Keywords: aircraft; gaussian process; learning control; via gaussian ... See more keywords
Gaussian process as complement to test functions for surrogate modeling
Sign Up to like & getrecommendations! Published in 2020 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-019-02441-1
Abstract: It is common for papers on surrogate fitting to select test functions for testing algorithms. This raises the issue of how well the algorithms generalize to other functions. This editorial proposes as a possible complement… read more here.
Keywords: test; test functions; generate random; decay rates ... See more keywords
A gaussian process framework for solving forward and inverse problems involving nonlinear partial differential equations
Sign Up to like & getrecommendations! Published in 2024 at "Computational Mechanics"
DOI: 10.1007/s00466-024-02559-0
Abstract: Physics-informed machine learning (PIML) has emerged as a promising alternative to conventional numerical methods for solving partial differential equations (PDEs). PIML models are increasingly built via deep neural networks (NNs) whose architecture and training process… read more here.
Keywords: gaussian process; differential equations; partial differential; process framework ... See more keywords
Gaussian process for estimating parameters of partial differential equations and its application to the Richards equation
Sign Up to like & getrecommendations! Published in 2019 at "Stochastic Environmental Research and Risk Assessment"
DOI: 10.1007/s00477-019-01709-8
Abstract: This paper proposes a new collocation method for estimating parameters of a partial differential equation (PDE), which uses Gaussian process (GP) as a basis function and is termed as Gaussian process for partial differential equation… read more here.
Keywords: partial differential; estimating parameters; method; equation ... See more keywords
Seismic vulnerability of above-ground storage tanks with unanchored support conditions for Na-tech risks based on Gaussian process regression
Sign Up to like & getrecommendations! Published in 2020 at "Bulletin of Earthquake Engineering"
DOI: 10.1007/s10518-020-00960-7
Abstract: This paper aims to investigate the seismic vulnerability of an existing unanchored steel storage tank ideally installed in a refinery in Sicily (Italy), along the lines of performance-based earthquake engineering. Tank performance is estimated by… read more here.
Keywords: storage; process regression; based gaussian; vulnerability ... See more keywords
Gaussian Process Emulators for Computer Experiments with Inequality Constraints
Sign Up to like & getrecommendations! Published in 2017 at "Mathematical Geosciences"
DOI: 10.1007/s11004-017-9673-2
Abstract: Physical phenomena are observed in many fields (science and engineering) and are often studied by time-consuming computer codes. These codes are analyzed with statistical models, often called emulators. In many situations, the physical system (computer… read more here.
Keywords: inequality constraints; inequality; computer; constraints gaussian ... See more keywords