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. 1606.08577
  4. Cited By
Reliability analysis of high-dimensional models using low-rank tensor
  approximations

Reliability analysis of high-dimensional models using low-rank tensor approximations

28 June 2016
K. Konakli
Bruno Sudret
ArXiv (abs)PDFHTML

Papers citing "Reliability analysis of high-dimensional models using low-rank tensor approximations"

4 / 4 papers shown
Title
Probabilistic partition of unity networks for high-dimensional
  regression problems
Probabilistic partition of unity networks for high-dimensional regression problems
Tiffany Fan
N. Trask
M. DÉlia
Eric F. Darve
60
1
0
06 Oct 2022
Grassmannian diffusion maps based surrogate modeling via geometric
  harmonics
Grassmannian diffusion maps based surrogate modeling via geometric harmonics
K. R. D. dos Santos
Dimitris G. Giovanis
Katiana Kontolati
Dimitrios Loukrezis
Michael D. Shields
49
9
0
28 Sep 2021
Sequential active learning of low-dimensional model representations for
  reliability analysis
Sequential active learning of low-dimensional model representations for reliability analysis
Max Ehre
I. Papaioannou
Bruno Sudret
D. Štraub
65
10
0
08 Jun 2021
An active-learning algorithm that combines sparse polynomial chaos
  expansions and bootstrap for structural reliability analysis
An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis
S. Marelli
Bruno Sudret
46
232
0
05 Sep 2017
1