ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2505.19737
  4. Cited By
Weighted Leave-One-Out Cross Validation

Weighted Leave-One-Out Cross Validation

26 May 2025
L. Pronzato
M. Rendas
ArXivPDFHTML

Papers citing "Weighted Leave-One-Out Cross Validation"

9 / 9 papers shown
Title
Comparing Scale Parameter Estimators for Gaussian Process Interpolation
  with the Brownian Motion Prior: Leave-One-Out Cross Validation and Maximum
  Likelihood
Comparing Scale Parameter Estimators for Gaussian Process Interpolation with the Brownian Motion Prior: Leave-One-Out Cross Validation and Maximum Likelihood
Masha Naslidnyk
Motonobu Kanagawa
Toni Karvonen
Maren Mahsereci
GP
28
0
0
14 Jul 2023
Model predictivity assessment: incremental test-set selection and
  accuracy evaluation
Model predictivity assessment: incremental test-set selection and accuracy evaluation
E. Fekhari
Bertrand Iooss
Joseph Muré
L. Pronzato
M. Rendas
52
13
0
08 Jul 2022
Maximum Likelihood Estimation in Gaussian Process Regression is
  Ill-Posed
Maximum Likelihood Estimation in Gaussian Process Regression is Ill-Posed
Toni Karvonen
Chris J. Oates
GP
26
26
0
17 Mar 2022
Gaussian Process Regression in the Flat Limit
Gaussian Process Regression in the Flat Limit
Simon Barthelmé
P. Amblard
Nicolas M Tremblay
K. Usevich
GP
25
5
0
04 Jan 2022
Quasi-uniform designs with optimal and near-optimal uniformity constant
Quasi-uniform designs with optimal and near-optimal uniformity constant
Lin Teng
Runqi Meng
33
5
0
20 Dec 2021
Cross-validation: what does it estimate and how well does it do it?
Cross-validation: what does it estimate and how well does it do it?
Stephen Bates
Trevor Hastie
Robert Tibshirani
UQCV
62
275
0
01 Apr 2021
Fast calculation of Gaussian Process multiple-fold cross-validation
  residuals and their covariances
Fast calculation of Gaussian Process multiple-fold cross-validation residuals and their covariances
D. Ginsbourger
Cedric Scharer
16
7
0
08 Jan 2021
Maximum likelihood estimation and uncertainty quantification for
  Gaussian process approximation of deterministic functions
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions
Toni Karvonen
George Wynne
Filip Tronarp
Chris J. Oates
Simo Särkkä
55
39
0
29 Jan 2020
Cross Validation and Maximum Likelihood estimations of hyper-parameters
  of Gaussian processes with model misspecification
Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification
François Bachoc
62
227
0
18 Jan 2013
1