HomePosts Tagged "gaussian process"

Tag Archives: gaussian process

New article: Solution of Inverse Problems with Limited Solver Evaluations: a Bayesian perspective

Article: Bilionis I, Zabaras N; (2014) Solution of Inverse Problems with Limited Solver Evaluations: a Bayesian perspective. Inverse Problems, 30(1); 352-373 DOI Abstract: Solving inverse problems based on computationally demanding forward models is ubiquitously ...
Read More

January 16, 2014Uncategorizedbayesian, epistemic uncertainty, gaussian process, inverse problems, reservoir engineering, Sequential Monte Carlo, surrogate model

New article: Multi-output Separable Gaussian Process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification

Article: Bilionis I, Zabaras N, Konomi BA, and Lin G, (2013) Multi-output Separable Gaussian Process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification. J. of Computational Physics, 241; 212-239 DOI Abstract: Computer codes ...
Read More

May 15, 2013Uncategorizedbayesian, gaussian process, Kronecker product, Separable covariance function, stochastic partial differential equations, Surrogate models, uncertainty quantification

New article: Multi-output local Gaussian process regression: Applications to uncertainty quantification

Article: Bilionis I and Zabaras N (2012). “Multi-output local Gaussian process regression: Applications to uncertainty quantification.” Journal of Computational Physics 231(17): 5718-5746. DOI Abstract: We develop an efficient, Bayesian Uncertainty Quantification framework using a ...
Read More

July 15, 2012Uncategorizedadaptivity, bayesian, collocation method, design, gaussian process, generalized polynomial chaos, models, multi-element, multi-output, random input data, stochastic differential-equations, stochastic partial differential equations, uncertainty quantification

menu

MAE Publications and Papers

Sibley School of Mechanical and Aerospace Engineering

Posts Tagged: gaussian process

Tag Archives: gaussian process

New article: Solution of Inverse Problems with Limited Solver Evaluations: a Bayesian perspective

New article: Multi-output Separable Gaussian Process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification

New article: Multi-output local Gaussian process regression: Applications to uncertainty quantification