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"Implementation issues in approximate methods for stochastic Hodgkin–Huxley models," Annals of Biomedical Engineering 35(2):355–358.
E, D. Liu, E. Vanden-Eijnden, Analysis of multiscale methods for stochastic differential equations, Commun.
Based on a technique used in [Müller, A., Stoyan, D., 2002. Comparison Methods for Stochastic Models and Risks.
The class of strong stochastic Runge Kutta methods for stochastic differential equations (SDEs) due to Rößler is considered.
Motivated by this, considerable research effort has been devoted to the development of modeling, analysis and control methods for stochastic hybrid systems.
This paper introduces the concept of distribution distance for the measurement of errors in exact and approximate methods for stochastic simulation of chemically reacting systems.
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Kingma, D. and Ba, J. Adam: a method for stochastic optimization.
Kingma, D. P. & Ba, J. Adam: a method for stochastic optimization.
A parameter estimation method for stochastic rainfall-runoff models is presented.
We present a new method for stochastic shape optimisation of engineering structures.
In this paper we investigate a stochastic multi-symplectic method for stochastic Maxwell equations with additive noise.
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