We develop a general convergence analysis for a class of inexact Newton-type regularizations for stably solving nonlinear ill-posed problems. Each of the methods under consideration consists of two components: the outer Newton iteration and an inner regularization scheme which, applied to the linearized system, provides the update. In this paper we give a novel and unified convergence analysis which is not confined to a specific inner regularization scheme but applies to a multitude of schemes including Landweber and steepest decent iterations, iterated Tikhonov method, and method of conjugate gradients
One can generate trajectories to simulate a system of chemical reactions using either Gillespie's di...
In this paper we examine the different formulations of Gillespie's stochastic simulation algorithm (...
We consider a general class of high order weak approximation schemes for stochastic differential equ...
We develop a general convergence analysis for a class of inexact Newton-type regularizations for sta...
International audienceWe consider linear and nonlinear reaction-diffusion problems, and their time d...
We develop a general convergence analysis for a class of inexact Newton-type regularizations for sta...
Background Biochemical systems with relatively low numbers of components must be simulated stochasti...
Stochastic models are widely used in the simulation of biochemical systems at a cellular level. For ...
There are two fundamental ways to view coupled systems of chemical equations: as continuous, repres...
Background: In this paper, we present a framework for improving the accuracy of fixed-step methods...
Biochemical processes in living cells are comprised of reactions with vastly varying speeds and mole...
Many biochemical processes at the sub-cellular level involve a small number of molecules. The local ...
BACKGROUND: In this paper, we present a framework for improving the accuracy of fixed-step methods f...
In cellular reaction systems, events often happen at different time and abundance scales. It is poss...
We present an effective procedure for selecting the stepsize in the binomial $\tau$-leap method, whi...
One can generate trajectories to simulate a system of chemical reactions using either Gillespie's di...
In this paper we examine the different formulations of Gillespie's stochastic simulation algorithm (...
We consider a general class of high order weak approximation schemes for stochastic differential equ...
We develop a general convergence analysis for a class of inexact Newton-type regularizations for sta...
International audienceWe consider linear and nonlinear reaction-diffusion problems, and their time d...
We develop a general convergence analysis for a class of inexact Newton-type regularizations for sta...
Background Biochemical systems with relatively low numbers of components must be simulated stochasti...
Stochastic models are widely used in the simulation of biochemical systems at a cellular level. For ...
There are two fundamental ways to view coupled systems of chemical equations: as continuous, repres...
Background: In this paper, we present a framework for improving the accuracy of fixed-step methods...
Biochemical processes in living cells are comprised of reactions with vastly varying speeds and mole...
Many biochemical processes at the sub-cellular level involve a small number of molecules. The local ...
BACKGROUND: In this paper, we present a framework for improving the accuracy of fixed-step methods f...
In cellular reaction systems, events often happen at different time and abundance scales. It is poss...
We present an effective procedure for selecting the stepsize in the binomial $\tau$-leap method, whi...
One can generate trajectories to simulate a system of chemical reactions using either Gillespie's di...
In this paper we examine the different formulations of Gillespie's stochastic simulation algorithm (...
We consider a general class of high order weak approximation schemes for stochastic differential equ...