ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 0804.0723
  4. Cited By
Estimating deformations of isotropic Gaussian random fields on the plane

Estimating deformations of isotropic Gaussian random fields on the plane

4 April 2008
E. Anderes
Michael L. Stein
ArXiv (abs)PDFHTML

Papers citing "Estimating deformations of isotropic Gaussian random fields on the plane"

15 / 15 papers shown
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian
  Processes
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian ProcessesAPL Machine Learning (AML), 2023
M. Noack
Hengrui Luo
M. Risser
GP
454
18
0
18 Sep 2023
Learning the regularity of multivariate functional data
Learning the regularity of multivariate functional data
Omar Kassi
N. Klutchnikoff
V. Patilea
296
3
0
26 Jul 2023
Mixtures of Gaussian process experts based on kernel stick-breaking
  processes
Mixtures of Gaussian process experts based on kernel stick-breaking processes
Yuji Saikai
Khue-Dung Dang
181
0
0
26 Apr 2023
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning
Sparse Spectrum Warped Input Measures for Nonstationary Kernel LearningNeural Information Processing Systems (NeurIPS), 2020
A. Tompkins
Rafael Oliveira
F. Ramos
260
8
0
09 Oct 2020
The SPDE Approach to Matérn Fields: Graph Representations
The SPDE Approach to Matérn Fields: Graph RepresentationsStatistical Science (Statist. Sci.), 2020
D. Sanz-Alonso
Ruiyi Yang
537
22
0
16 Apr 2020
Deep Compositional Spatial Models
Deep Compositional Spatial ModelsJournal of the American Statistical Association (JASA), 2019
A. Zammit‐Mangion
T. L. J. Ng
Quan Vu
Maurizio Filippone
224
65
0
06 Jun 2019
Posterior Inference for Sparse Hierarchical Non-stationary Models
Posterior Inference for Sparse Hierarchical Non-stationary Models
K. Monterrubio-Gómez
L. Roininen
S. Wade
Theo Damoulas
Mark Girolami
387
28
0
04 Apr 2018
Amplitude and phase variation of point processes
Amplitude and phase variation of point processes
V. Panaretos
Y. Zemel
232
109
0
29 Mar 2016
Estimating the smoothness of a Gaussian random field from irregularly
  spaced data via higher-order quadratic variations
Estimating the smoothness of a Gaussian random field from irregularly spaced data via higher-order quadratic variations
Wei-Liem Loh
72
20
0
29 Oct 2015
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
Non-Stationary Gaussian Process Regression with Hamiltonian Monte CarloInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2015
Markus Heinonen
Henrik Mannerstrom
Juho Rousu
Samuel Kaski
Harri Lähdesmäki
242
118
0
18 Aug 2015
Gaussian Random Functional Dynamic Spatio-Temporal Modeling of Discrete
  Time Spatial Time Series Data
Gaussian Random Functional Dynamic Spatio-Temporal Modeling of Discrete Time Spatial Time Series Data
S. Guha
S. Bhattacharya
206
1
0
26 May 2014
Input Warping for Bayesian Optimization of Non-stationary Functions
Input Warping for Bayesian Optimization of Non-stationary FunctionsInternational Conference on Machine Learning (ICML), 2014
Jasper Snoek
Kevin Swersky
R. Zemel
Ryan P. Adams
512
259
0
05 Feb 2014
Fractal and Smoothness Properties of Space-Time Gaussian Models
Fractal and Smoothness Properties of Space-Time Gaussian Models
Y. Xue
Yimin Xiao
273
45
0
01 Dec 2009
On the consistent separation of scale and variance for Gaussian random
  fields
On the consistent separation of scale and variance for Gaussian random fields
E. Anderes
393
76
0
20 Jun 2009
Consistent estimates of deformed isotropic Gaussian random fields on the
  plane
Consistent estimates of deformed isotropic Gaussian random fields on the plane
E. Anderes
S. Chatterjee
622
31
0
01 Oct 2007
1
Page 1 of 1