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. 2105.05539
  4. Cited By
A new framework for experimental design using Bayesian Evidential
  Learning: the case of wellhead protection area

A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection area

12 May 2021
Robin Thibaut
E. Laloy
T. Hermans
ArXiv (abs)PDFHTML

Papers citing "A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection area"

4 / 4 papers shown
Title
Optimal Bayesian experimental design for subsurface flow problems
Optimal Bayesian experimental design for subsurface flow problems
Alexander Tarakanov
A. Elsheikh
39
10
0
10 Aug 2020
Seismic Bayesian evidential learning: Estimation and uncertainty
  quantification of sub-resolution reservoir properties
Seismic Bayesian evidential learning: Estimation and uncertainty quantification of sub-resolution reservoir properties
A. Pradhan
T. Mukerji
21
28
0
14 May 2019
Surrogate-Based Bayesian Inverse Modeling of the Hydrological System: An
  Adaptive Approach Considering Surrogate Approximation Error
Surrogate-Based Bayesian Inverse Modeling of the Hydrological System: An Adaptive Approach Considering Surrogate Approximation Error
Jiangjiang Zhang
Q. Zheng
Dingjiang Chen
Laosheng Wu
L. Zeng
70
36
0
10 Jul 2018
Pyrcca: regularized kernel canonical correlation analysis in Python and
  its applications to neuroimaging
Pyrcca: regularized kernel canonical correlation analysis in Python and its applications to neuroimaging
Natalia Y. Bilenko
J. Gallant
60
82
0
05 Mar 2015
1