113 citations · 302 across the 23 of their papers we have counts for
24 papers
Using a library of chemical reactions to fit systems of ordinary differential equations to agent-based models: a machine learning approach
Pamela M. Burrage, Hasitha N. Weerasinghe, Kevin Burrage
In this paper we introduce a new method based on a library of chemical reactions for constructing a system of ordinary differential equations from stochastic simulations arising fr…
Digital Twinning of the Human Ventricular Activation Sequence to Clinical 12-lead ECGs and Magnetic Resonance Imaging Using Realistic Purkinje Networks for in Silico Clinical Trials
Julia Camps, Lucas Arantes Berg, Zhinuo Jenny Wang +12
Cardiac in silico clinical trials can virtually assess the safety and efficacy of therapies using human-based modelling and simulation. These technologies can provide mechanistic e…
The Fisher Geometry and Geodesics of the Multivariate Normals, without Differential Geometry
Brodie A. J. Lawson, Kevin Burrage, Kerrie Mengersen +1
Choosing the Fisher information as the metric tensor for a Riemannian manifold provides a powerful yet fundamental way to understand statistical distribution families. Distances al…
Formulae for mixed moments of Wiener processes and a stochastic area integral
Yoshio Komori, Guoguo Yang, Kevin Burrage
This paper deals with the expectation of monomials with respect to the stochastic area integral $A_{1,2}(t,t+h)=\int_{t}^{t+h}\int_{t}^{s}{\rm d} W_{1}(r){\rm d} W_{2}(s) -\int_{t}…
Stability switching in Lotka-Volterra and Ricker-type predator-prey systems with arbitrary step size
Shamika P. Kekulthotuwage Don, Kevin Burrage, Kate J. Helmstedt +1
Dynamical properties of numerically approximated discrete systems may become inconsistent with those of the corresponding continuous-time system. We present a qualitative analysis…
Analysis of sloppiness in model simulations: unveiling parameter uncertainty when mathematical models are fitted to data
Gloria M. Monsalve-Bravo, Brodie A. J. Lawson, Christopher Drovandi +7
This work introduces a comprehensive approach to assess the sensitivity of model outputs to changes in parameter values, constrained by the combination of prior beliefs and data. T…