Explicit Estimation of Derivatives from Data and Differential Equations
by Gaussian Process Regression

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Explicit Estimation of Derivatives from Data and Differential Equations by Gaussian Process Regression

13 April 2020

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Papers citing "Explicit Estimation of Derivatives from Data and Differential Equations by Gaussian Process Regression"

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Title
Model-Embedded Gaussian Process Regression for Parameter Estimation in Dynamical System Ying Zhou Jinglai Li Xiang Zhou Hongqiao Wang 51 0 0 18 Sep 2024
The Weak Form Is Stronger Than You Think Daniel Messenger April Tran Vanja M. Dukic David M. Bortz 94 3 0 10 Sep 2024
Data-Driven Model Selections of Second-Order Particle Dynamics via Integrating Gaussian Processes with Low-Dimensional Interacting Structures Jinchao Feng Charles Kulick Sui Tang 112 2 0 01 Nov 2023
Learning Collective Behaviors from Observation Jinchao Feng Ming Zhong 72 2 0 01 Nov 2023
Direct Estimation of Parameters in ODE Models Using WENDy: Weak-form Estimation of Nonlinear Dynamics David M. Bortz Daniel Messenger Vanja M. Dukic 64 18 0 26 Feb 2023
PAGP: A physics-assisted Gaussian process framework with active learning for forward and inverse problems of partial differential equations Jiahao Zhang Shiqi Zhang Guang Lin 81 3 0 06 Apr 2022
Active Learning for Saddle Point Calculation Shuting Gu Hongqiao Wang Xiaoping Zhou 36 5 0 10 Aug 2021
Learning particle swarming models from data with Gaussian processes Jinchao Feng Charles Kulick Yunxiang Ren Sui Tang 49 6 0 04 Jun 2021
Inferring the unknown parameters in Differential Equation by Gaussian Process Regression with Constraint Ying Zhou Hongqiao Wang 14 4 0 22 Nov 2020