Measuring the robustness of Gaussian processes to kernel choice

11 June 2021

Papers citing "Measuring the robustness of Gaussian processes to kernel choice"

8 / 8 papers shown

Title
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness George Wynne F. Briol Mark Girolami 47 56 0 29 Jan 2020
Convergence of Gaussian Process Regression with Estimated Hyper-parameters and Applications in Bayesian Inverse Problems A. Teckentrup 27 66 0 31 Aug 2019
Robustness Guarantees for Bayesian Inference with Gaussian Processes L. Cardelli Marta Kwiatkowska Luca Laurenti A. Patané AAML 48 52 0 17 Sep 2018
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 113 1,091 0 01 Nov 2017
Estimation and Prediction using generalized Wendland Covariance Functions under fixed domain asymptotics M. Bevilacqua Tarik Faouzi Reinhard Furrer Emilio Porcu 63 74 0 23 Jul 2016
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 216 885 0 06 Nov 2015
Structure Discovery in Nonparametric Regression through Compositional Kernel Search David Duvenaud J. Lloyd Roger C. Grosse J. Tenenbaum Zoubin Ghahramani 80 509 0 20 Feb 2013
Gaussian Process Kernels for Pattern Discovery and Extrapolation A. Wilson Ryan P. Adams GP 66 606 0 18 Feb 2013