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Convergence of Gaussian Process Regression with Estimated Hyper-parameters and Applications in Bayesian Inverse Problems

31 August 2019

Papers citing "Convergence of Gaussian Process Regression with Estimated Hyper-parameters and Applications in Bayesian Inverse Problems"

31 / 31 papers shown

Title
Gaussian Processes Sampling with Sparse Grids under Additive Schwarz Preconditioner Haoyuan Chen Rui Tuo 67 0 0 01 Aug 2024
Conditional Bayesian Quadrature Zonghao Chen Masha Naslidnyk Arthur Gretton F. Briol TPM 84 3 0 24 Jun 2024
On Safety in Safe Bayesian Optimization Christian Fiedler Johanna Menn Lukas Kreisköther Sebastian Trimpe 79 11 0 19 Mar 2024
PMBO: Enhancing Black-Box Optimization through Multivariate Polynomial Surrogates Janina Schreiber Pau Batlle D. Wicaksono Michael Hecht 79 0 0 12 Mar 2024
Deep Horseshoe Gaussian Processes Ismael Castillo Thibault Randrianarisoa BDL UQCV 106 5 0 04 Mar 2024
A Bayesian approach with Gaussian priors to the inverse problem of source identification in elliptic PDEs Matteo Giordano 43 0 0 29 Feb 2024
Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration Hwanwoo Kim D. Sanz-Alonso 79 3 0 30 Jan 2024
Dynamical System Identification, Model Selection and Model Uncertainty Quantification by Bayesian Inference R. Niven Laurent Cordier Ali Mohammad-Djafari Markus Abel M. Quade 96 6 0 30 Jan 2024
Gaussian Process Regression under Computational and Epistemic Misspecification D. Sanz-Alonso Ruiyi Yang 60 1 0 14 Dec 2023
Robust and Conjugate Gaussian Process Regression Matias Altamirano F. Briol Jeremias Knoblauch 82 13 0 01 Nov 2023
Gaussian processes for Bayesian inverse problems associated with linear partial differential equations Tianming Bai A. Teckentrup K. Zygalakis 68 13 0 17 Jul 2023
Stochastic PDE representation of random fields for large-scale Gaussian process regression and statistical finite element analysis Kim Jie Koh F. Cirak AI4CE 60 12 0 23 May 2023
Bayesian Posterior Perturbation Analysis with Integral Probability Metrics A. Garbuno-Iñigo T. Helin Franca Hoffmann Bamdad Hosseini 123 10 0 02 Mar 2023
Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures T. Helin Andrew M. Stuart A. Teckentrup K. Zygalakis 62 5 0 09 Feb 2023
Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference Ayush Bharti Masha Naslidnyk Oscar Key Samuel Kaski F. Briol 127 15 0 27 Jan 2023
Antenna Array Calibration Via Gaussian Process Models Sergey S. Tambovskiy Gábor Fodor H. Tullberg 24 1 0 16 Jan 2023
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems Lianghao Cao Thomas O'Leary-Roseberry Prashant K. Jha J. Oden Omar Ghattas 67 26 0 06 Oct 2022
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization Shouri Hu Haowei Wang Zhongxiang Dai K. H. Low Szu Hui Ng 58 4 0 10 May 2022
Maximum Likelihood Estimation in Gaussian Process Regression is Ill-Posed Toni Karvonen Chris J. Oates GP 73 26 0 17 Mar 2022
On Average-Case Error Bounds for Kernel-Based Bayesian Quadrature Xu Cai Chi Thanh Lam Jonathan Scarlett 57 3 0 22 Feb 2022
Error analysis for a statistical finite element method Toni Karvonen F. Cirak Mark Girolami 17 4 0 19 Jan 2022
Estimation of the Scale Parameter for a Misspecified Gaussian Process Model Toni Karvonen 50 4 0 06 Oct 2021
Optimal Order Simple Regret for Gaussian Process Bandits Sattar Vakili N. Bouziani Sepehr Jalali A. Bernacchia Da-shan Shiu 99 55 0 20 Aug 2021
Measuring the robustness of Gaussian processes to kernel choice William T. Stephenson S. Ghosh Tin D. Nguyen Mikhail Yurochkin Sameer K. Deshpande Tamara Broderick GP 35 11 0 11 Jun 2021
A Fast and Calibrated Computer Model Emulator: An Empirical Bayes Approach Vojtech Kejzlar Mookyong Son Shrijita Bhattacharya T. Maiti 25 6 0 11 Aug 2020
Bayesian Probabilistic Numerical Integration with Tree-Based Models Harrison Zhu Xing Liu Ruya Kang Zhichao Shen Seth Flaxman F. Briol TPM 42 5 0 09 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 71 35 0 09 Jun 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
Regret Bounds for Noise-Free Kernel-Based Bandits Sattar Vakili 67 3 0 12 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
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness George Wynne F. Briol Mark Girolami 82 56 0 29 Jan 2020