Learning "best" kernels from data in Gaussian process regression. With
application to aerodynamics

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Learning "best" kernels from data in Gaussian process regression. With application to aerodynamics

3 June 2022

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Papers citing "Learning "best" kernels from data in Gaussian process regression. With application to aerodynamics"

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Title
Solving and Learning Nonlinear PDEs with Gaussian Processes Yifan Chen Bamdad Hosseini H. Owhadi Andrew M. Stuart 79 157 0 24 Mar 2021
Learning dynamical systems from data: a simple cross-validation perspective B. Hamzi H. Owhadi 69 41 0 09 Jul 2020
Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation Yifan Chen H. Owhadi Andrew M. Stuart 103 31 0 22 May 2020
Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows G. Yoo H. Owhadi 69 21 0 19 Feb 2020
Kernel Flows: from learning kernels from data into the abyss H. Owhadi G. Yoo 88 90 0 13 Aug 2018
Asymptotic normality and efficiency of two Sobol index estimators Alexandre Janon T. Klein Agnès Lagnoux-Renaudie M. Nodet Clémentine Prieur 60 231 0 26 Mar 2013
Calculations of Sobol indices for the Gaussian process metamodel A. Marrel Bertrand Iooss Béatrice Laurent O. Roustant 170 338 0 07 Feb 2008

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