26 citations · 33 across the 7 of their papers we have counts for
6 papers · 1 filter
Variational autoencoder for inference of nonlinear mixed effect models based on ordinary differential equations
Zhe Li, Mélanie Prague, Rodolphe Thiébaut +1
We propose a variational autoencoder (VAE) approach for parameter estimation in nonlinear mixed-effects models based on ordinary differential equations (NLME-ODEs) using longitudin…
Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control approach
Quentin Clairon, Chloé Pasin, Irene Balelli +2
We present a parameter estimation method for nonlinear mixed effect models based on ordinary differential equations (NLME-ODEs). The method presented here aims at regularizing the…
A regularization method for the parameter estimation problem in ordinary differential equations via discrete optimal control theory
Quentin Clairon
We present a parameter estimation method in Ordinary Differential Equation (ODE) models. Due to complex relationships between parameters and states the use of standard techniques s…
Parametric Estimation of Ordinary Differential Equations with Orthogonality Conditions
Nicolas J-B Brunel, Quentin Clairon, Florence d'Alche-Buc
Differential equations are commonly used to model dynamical deterministic systems in applications. When statistical parameter estimation is required to calibrate theoretical models…
State and Parameter Estimation of Partially Observed Linear Ordinary Differential Equations with Deterministic Optimal Control
Quentin Clairon, Nicolas Brunel
Ordinary Differential Equations are a simple but powerful framework for modeling complex systems. Parameter estimation from times series can be done by Nonlinear Least Squares (or…
A Tracking Approach to Parameter Estimation in Linear Ordinary Differential Equations
Nicolas Brunel, Quentin Clairon
Ordinary Differential Equations are widespread tools to model chemical, physical, biological process but they usually rely on parameters which are of critical importance in terms o…