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Maximum Likelihood Estimation in Gaussian Process Regression is Ill-Posed
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Maximum Likelihood Estimation in Gaussian Process Regression is Ill-Posed

Toni Karvonen
Chris J. Oates
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Papers citing "Maximum Likelihood Estimation in Gaussian Process Regression is Ill-Posed"

5 / 5 papers shown
Title
Implementing Keyword Spotting on the MCUX947 Microcontroller with Integrated NPU
Petar Jakuš
Hrvoje Džapo
15
0
0
10 Jun 2025
Weighted Leave-One-Out Cross Validation
Weighted Leave-One-Out Cross Validation
L. Pronzato
M. Rendas
64
0
0
26 May 2025
Physics-based Reduced Order Modeling for Uncertainty Quantification of Guided Wave Propagation using Bayesian Optimization
Physics-based Reduced Order Modeling for Uncertainty Quantification of Guided Wave Propagation using Bayesian Optimization
G. Drakoulas
T. Gortsas
D. Polyzos
105
5
0
18 Jul 2023
HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes
HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes
Z. Fan
Xinran Han
Zehao Wang
91
4
0
20 Dec 2022
GParareal: A time-parallel ODE solver using Gaussian process emulation
GParareal: A time-parallel ODE solver using Gaussian process emulation
K. Pentland
M. Tamborrino
Timothy John Sullivan
J. Buchanan
Lynton C. Appel
48
8
0
31 Jan 2022