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Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification

18 January 2013

Papers citing "Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification"

50 / 64 papers shown

Title
Weighted Leave-One-Out Cross Validation L. Pronzato M. Rendas 72 0 0 26 May 2025
Adaptive Replication Strategies in Trust-Region-Based Bayesian Optimization of Stochastic Functions Mickael Binois Jeffrey Larson 122 0 0 29 Apr 2025
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal Juliusz Ziomek Masaki Adachi Michael A. Osborne 93 1 0 14 Oct 2024
Multifidelity Cross-validation Sudharshan Ashwin Renganathan Kade Carlson 85 0 0 01 Jul 2024
Asymptotic analysis for covariance parameter estimation of Gaussian processes with functional inputs Lucas Reding A. F. López-Lopera François Bachoc 70 1 0 26 Apr 2024
Robust and Conjugate Gaussian Process Regression Matias Altamirano F. Briol Jeremias Knoblauch 84 13 0 01 Nov 2023
Comparing Scale Parameter Estimators for Gaussian Process Interpolation with the Brownian Motion Prior: Leave-One-Out Cross Validation and Maximum Likelihood Masha Naslidnyk Motonobu Kanagawa Toni Karvonen Maren Mahsereci GP 50 1 0 14 Jul 2023
Provably Efficient Bayesian Optimization with Unknown Gaussian Process Hyperparameter Estimation Huong Ha Vu-Linh Nguyen Hung Tran-The Hongyu Zhang Xiuzhen Zhang Anton Van Den Hengel 73 1 0 12 Jun 2023
A comparison between Bayesian and ordinary kriging based on validation criteria: application to radiological characterisation Martin Wieskotten M. Crozet Bertrand Iooss C. Lacaux A. Marrel 45 10 0 12 May 2023
Learning non-stationary and discontinuous functions using clustering, classification and Gaussian process modelling M. Moustapha Bruno Sudret 56 9 0 30 Nov 2022
Bayesian Optimization with Conformal Prediction Sets Samuel Stanton Wesley J. Maddox A. Wilson 147 26 0 22 Oct 2022
Gaussian Processes on Distributions based on Regularized Optimal Transport François Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes GP OT 66 8 0 12 Oct 2022
Maximum Likelihood Estimation in Gaussian Process Regression is Ill-Posed Toni Karvonen Chris J. Oates GP 78 26 0 17 Mar 2022
Asymptotic Bounds for Smoothness Parameter Estimates in Gaussian Process Interpolation Toni Karvonen 66 3 0 10 Mar 2022
Multi-objective robust optimization using adaptive surrogate models for problems with mixed continuous-categorical parameters M. Moustapha A. Galimshina G. Habert Bruno Sudret 61 11 0 03 Mar 2022
Bounds in $L^1$ Wasserstein distance on the normal approximation of general M-estimators François Bachoc M. Fathi 41 0 0 18 Nov 2021
Estimation of the Scale Parameter for a Misspecified Gaussian Process Model Toni Karvonen 50 4 0 06 Oct 2021
Multi-fidelity surrogate modeling for time-series outputs Baptiste Kerleguer 37 4 0 23 Sep 2021
Importance sampling based active learning for parametric seismic fragility curve estimation Clement Gauchy C. Feau Josselin Garnier 42 4 0 09 Sep 2021
Parameter selection in Gaussian process interpolation: an empirical study of selection criteria S. Petit Julien Bect Paul Feliot E. Vázquez 62 11 0 13 Jul 2021
Robust Prediction Interval estimation for Gaussian Processes by Cross-Validation method Naoufal Acharki A. Bertoncello Josselin Garnier 25 12 0 09 Jun 2021
Scalable Cross Validation Losses for Gaussian Process Models M. Jankowiak Geoff Pleiss 65 6 0 24 May 2021
Lightweight Distributed Gaussian Process Regression for Online Machine Learning Zhenyuan Yuan Minghui Zhu 50 4 0 11 May 2021
Fast calculation of Gaussian Process multiple-fold cross-validation residuals and their covariances D. Ginsbourger Cedric Scharer 45 9 0 08 Jan 2021
Asymptotic analysis of maximum likelihood estimation of covariance parameters for Gaussian processes: an introduction with proofs François Bachoc 54 13 0 15 Sep 2020
A two-level Kriging-based approach with active learning for solving time-variant risk optimization problems H. M. Kroetz M. Moustapha A. Beck Bruno Sudret AI4CE 31 40 0 08 Jul 2020
Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation Yifan Chen H. Owhadi Andrew M. Stuart 111 31 0 22 May 2020
Cross-validation based adaptive sampling for Gaussian process models Hossein Mohammadi P. Challenor D. Williamson M. Goodfellow 40 12 0 04 May 2020
The ICSCREAM methodology: Identification of penalizing configurations in computer experiments using screening and metamodel -- Applications in thermal-hydraulics A. M. CEA-DES Bertrand Iooss V. Chabridon 59 17 0 08 Apr 2020
Towards new cross-validation-based estimators for Gaussian process regression: efficient adjoint computation of gradients S. Petit Julien Bect Sébastien Da Veiga Paul Feliot E. Vázquez 51 8 0 26 Feb 2020
Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows G. Yoo H. Owhadi 74 21 0 19 Feb 2020
On the Inference of Applying Gaussian Process Modeling to a Deterministic Function Wei Cao 76 19 0 04 Feb 2020
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions Toni Karvonen George Wynne Filip Tronarp Chris J. Oates Simo Särkkä 104 39 0 29 Jan 2020
Parallel cross-validation: a scalable fitting method for Gaussian process models Florian Gerber D. Nychka 9 9 0 31 Dec 2019
Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes François Bachoc José Bétancourt Reinhard Furrer T. Klein 45 12 0 25 Nov 2019
Evolving Gaussian Process kernels from elementary mathematical expressions Ibai Roman Roberto Santana A. Mendiburu Jose A. Lozano 33 3 0 11 Oct 2019
Adaptive surrogate models for parametric studies J. Fuhg 38 8 0 12 May 2019
Surrogate-assisted reliability-based design optimization: a survey and a new general framework M. Moustapha Bruno Sudret AI4CE 13 2 0 10 Jan 2019
Gaussian processes with linear operator inequality constraints C. Agrell 74 39 0 10 Jan 2019
Extending classical surrogate modelling to high-dimensions through supervised dimensionality reduction: a data-driven approach C. Lataniotis S. Marelli Bruno Sudret 45 67 0 15 Dec 2018
Composite likelihood estimation for a gaussian process under fixed domain asymptotics François Bachoc M. Bevilacqua D. Velandia 51 12 0 24 Jul 2018
Maximum likelihood estimation for Gaussian processes under inequality constraints François Bachoc A. Lagnoux A. F. López-Lopera 87 24 0 10 Apr 2018
Interpolation error of misspecified Gaussian process regression A. Zaytsev Evgenia Romanenkova D. Ermilov 8 0 0 26 Mar 2018
Gaussian Processes indexed on the symmetric group: prediction and learning François Bachoc Baptiste Broto Fabrice Gamboa Jean-Michel Loubes 38 0 0 16 Mar 2018
Finite-dimensional Gaussian approximation with linear inequality constraints A. F. López-Lopera François Bachoc N. Durrande O. Roustant 133 67 0 20 Oct 2017
Replication or exploration? Sequential design for stochastic simulation experiments M. Binois Jiangeng Huang R. Gramacy M. Ludkovski 73 115 0 09 Oct 2017
The Gaussian process modelling module in UQLab C. Lataniotis S. Marelli Bruno Sudret GP 18 11 0 27 Sep 2017
Hierarchical Kriging for multi-fidelity aero-servo-elastic simulators - Application to extreme loads on wind turbines Imad Abdallah S. Marelli Bruno Sudret 36 32 0 22 Sep 2017
Large Scale Variable Fidelity Surrogate Modeling Evgeny Burnaev Alexey Zaytsev AI4CE 85 29 0 12 Jul 2017
Structural reliability analysis for p-boxes using multi-level meta-models R. Schöbi Bruno Sudret 28 101 0 10 May 2017