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Numerical issues in maximum likelihood parameter estimation for Gaussian
  process interpolation

Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation

24 January 2021
S. Basak
S. Petit
Julien Bect
E. Vázquez
ArXivPDFHTML

Papers citing "Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation"

3 / 3 papers shown
Title
A Global-Local Approximation Framework for Large-Scale Gaussian Process
  Modeling
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling
Akhil Vakayil
Roshan Joseph
30
2
0
17 May 2023
Numerically Stable Sparse Gaussian Processes via Minimum Separation
  using Cover Trees
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
Alexander Terenin
David R. Burt
A. Artemev
Seth Flaxman
Mark van der Wilk
C. Rasmussen
Hong Ge
58
7
0
14 Oct 2022
Fully Decentralized, Scalable Gaussian Processes for Multi-Agent
  Federated Learning
Fully Decentralized, Scalable Gaussian Processes for Multi-Agent Federated Learning
George P. Kontoudis
D. Stilwell
FedML
19
8
0
06 Mar 2022
1