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. 2008.04598
  4. Cited By
Uncertainty Quantification of Locally Nonlinear Dynamical Systems using
  Neural Networks

Uncertainty Quantification of Locally Nonlinear Dynamical Systems using Neural Networks

11 August 2020
Subhayan De
ArXiv (abs)PDFHTML

Papers citing "Uncertainty Quantification of Locally Nonlinear Dynamical Systems using Neural Networks"

3 / 3 papers shown
Title
A Bi-fidelity DeepONet Approach for Modeling Uncertain and Degrading
  Hysteretic Systems
A Bi-fidelity DeepONet Approach for Modeling Uncertain and Degrading Hysteretic Systems
Subhayan De
P. Brewick
87
0
0
25 Apr 2023
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using
  DeepONets
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets
Subhayan De
Matthew J. Reynolds
M. Hassanaly
Ryan N. King
Alireza Doostan
AI4CE
103
38
0
03 Apr 2022
Prediction of Ultrasonic Guided Wave Propagation in Solid-fluid and
  their Interface under Uncertainty using Machine Learning
Prediction of Ultrasonic Guided Wave Propagation in Solid-fluid and their Interface under Uncertainty using Machine Learning
Subhayan De
B. Hai
Alireza Doostan
M. Bause
30
2
0
30 Mar 2021
1