Many mathematical models in biology and physiology are represented by systems of nonlinear differential equations. In recent years these models have become increasingly large-scale and multiphysics, as increasing amounts of data are available on the properties and behaviour of biological systems. Often an observed behaviour of interest in a model may be written as a linear functional. A key question therefore is to determine which terms in the model have the greatest effect on functionals of interest.An approach for answering this question has recently been developed, called model reduction using a posteriori analysis. The method was initially developed for systems of nonlinear initial value ordinary differential equations, and automaticall...
This thesis show the results of available techniques to reduce the size of a nonlinear DAE which are...
Model reduction is a central problem in mathematical biology. Reduced order models enable modeling o...
In life sciences, deriving insights from dynamic models can be challenging due to the large number o...
Many mathematical models in biology and physiology are represented by systems of nonlinear different...
Mathematical models in biology and physiology are often represented by large systems of non-linear o...
Mathematical models in biology and physiology are often represented by large systems of non–linear o...
Mathematical models are used for simulations and predictions of various phenomena and processes that...
tutorial talk for AB 2008.International audienceAmong all the modeling approaches dedicated to cellu...
Differential algebra is an algebraic theory for studying systems of polynomial ordinary differential...
Extended abstract of an invited talk at Differential Algebra and related Computer Algebra (Catania, ...
The application of ordinary differential equations to modelling the physical world is extensive and ...
Ordinary differential equations (ODEs) are widely used to model physical, chemical and biological pr...
A mathematical model of a dynamical process, often in the form of a system of differential equations...
Models of complex systems often consist of state variables with structurally similar dynamics that d...
This thesis addresses the reduction of differential-algebraic equation (DAE) systems. Modelling of p...
This thesis show the results of available techniques to reduce the size of a nonlinear DAE which are...
Model reduction is a central problem in mathematical biology. Reduced order models enable modeling o...
In life sciences, deriving insights from dynamic models can be challenging due to the large number o...
Many mathematical models in biology and physiology are represented by systems of nonlinear different...
Mathematical models in biology and physiology are often represented by large systems of non-linear o...
Mathematical models in biology and physiology are often represented by large systems of non–linear o...
Mathematical models are used for simulations and predictions of various phenomena and processes that...
tutorial talk for AB 2008.International audienceAmong all the modeling approaches dedicated to cellu...
Differential algebra is an algebraic theory for studying systems of polynomial ordinary differential...
Extended abstract of an invited talk at Differential Algebra and related Computer Algebra (Catania, ...
The application of ordinary differential equations to modelling the physical world is extensive and ...
Ordinary differential equations (ODEs) are widely used to model physical, chemical and biological pr...
A mathematical model of a dynamical process, often in the form of a system of differential equations...
Models of complex systems often consist of state variables with structurally similar dynamics that d...
This thesis addresses the reduction of differential-algebraic equation (DAE) systems. Modelling of p...
This thesis show the results of available techniques to reduce the size of a nonlinear DAE which are...
Model reduction is a central problem in mathematical biology. Reduced order models enable modeling o...
In life sciences, deriving insights from dynamic models can be challenging due to the large number o...