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. 2011.10971
  4. Cited By
Inferring the unknown parameters in Differential Equation by Gaussian
  Process Regression with Constraint

Inferring the unknown parameters in Differential Equation by Gaussian Process Regression with Constraint

Computational and Applied Mathematics (CAM), 2020
22 November 2020
Ying Zhou
Hongqiao Wang
ArXiv (abs)PDFHTML

Papers citing "Inferring the unknown parameters in Differential Equation by Gaussian Process Regression with Constraint"

4 / 4 papers shown
Bayesian Nonlinear PDE Inference via Gaussian Process Collocation with Application to the Richards Equation
Bayesian Nonlinear PDE Inference via Gaussian Process Collocation with Application to the Richards Equation
Yumo Yang
Anass Ben Bouazza
Xuejun Dong
Quan Zhou
96
0
0
27 Oct 2025
Are Statistical Methods Obsolete in the Era of Deep Learning? A Study of ODE Inverse Problems
Are Statistical Methods Obsolete in the Era of Deep Learning? A Study of ODE Inverse Problems
Skyler Wu
Shihao Yang
S. C. Kou
AI4CE
147
0
0
27 May 2025
Model-Embedded Gaussian Process Regression for Parameter Estimation in
  Dynamical System
Model-Embedded Gaussian Process Regression for Parameter Estimation in Dynamical System
Ying Zhou
Jinglai Li
Xiang Zhou
Hongqiao Wang
205
1
0
18 Sep 2024
Parameter Inference based on Gaussian Processes Informed by Nonlinear
  Partial Differential Equations
Parameter Inference based on Gaussian Processes Informed by Nonlinear Partial Differential Equations
Zhao-Xia Li
Shih-Feng Yang
Jeff Wu
419
6
0
22 Dec 2022
1
Page 1 of 1