research
∙
07/03/2023
Understanding the impact of numerical solvers on inference for differential equation models
Most ordinary differential equation (ODE) models used to describe biolog...
share
research
∙
02/06/2023
Empirical quantification of predictive uncertainty due to model discrepancy by training with an ensemble of experimental designs: an application to ion channel kinetics
When mathematical biology models are used to make quantitative predictio...
research
∙
10/04/2022
Autocorrelated measurement processes and inference for ordinary differential equation models of biological systems
Ordinary differential equation models are used to describe dynamic proce...
research
∙
11/10/2020
Using flexible noise models to avoid noise model misspecification in inference of differential equation time series models
When modelling time series, it is common to decompose observed variation...
research
∙
05/22/2020
Model Evidence with Fast Tree Based Quadrature
High dimensional integration is essential to many areas of science, rang...
research
∙
01/13/2020
Considering discrepancy when calibrating a mechanistic electrophysiology model
Uncertainty quantification (UQ) is a vital step in using mathematical mo...
research
∙
12/18/2018
