Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness

29 January 2020

Papers citing "Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness"

10 / 10 papers shown

Title
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis Yasamin Jalalian Juan Felipe Osorio Ramirez Alexander W. Hsu Bamdad Hosseini H. Owhadi 48 0 0 02 Mar 2025
Robust and Conjugate Gaussian Process Regression Matias Altamirano F. Briol Jeremias Knoblauch 28 10 0 01 Nov 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 34 4 0 09 Feb 2023
Bandit Convex Optimisation Revisited: FTRL Achieves $\tilde{O}(t^{1/2})$ Regret David Young D. Leith Georgios Iosifidis 23 0 0 01 Feb 2023
Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference Ayush Bharti Masha Naslidnyk Oscar Key Samuel Kaski F. Briol 42 12 0 27 Jan 2023
Antenna Array Calibration Via Gaussian Process Models Sergey S. Tambovskiy Gábor Fodor H. Tullberg 9 1 0 16 Jan 2023
Asymptotic Bounds for Smoothness Parameter Estimates in Gaussian Process Interpolation Toni Karvonen 27 1 0 10 Mar 2022
Meta-Learning Hypothesis Spaces for Sequential Decision-making Parnian Kassraie Jonas Rothfuss Andreas Krause OffRL 38 6 0 01 Feb 2022
Misspecified Gaussian Process Bandit Optimization Ilija Bogunovic Andreas Krause 57 43 0 09 Nov 2021
Non-smooth Bayesian Optimization in Tuning Problems Hengrui Luo J. Demmel Younghyun Cho Xin Li Yang Liu 25 13 0 15 Sep 2021