<--- Back to Details
First PageDocument Content
Mathematical analysis / Functional analysis / Metaphysics / Stochastic processes / Distribution / Stochastic simulation / Dynamical system
Date: 2016-07-05 04:52:12
Mathematical analysis
Functional analysis
Metaphysics
Stochastic processes
Distribution
Stochastic simulation
Dynamical system

A Stochastic Hybrid Approximation for Chemical Kinetics Based on the Linear Noise Approximation Luca Cardelli1,2 , Marta Kwiatkowska2 , and Luca Laurenti2 1

Add to Reading List

Source URL: qav.comlab.ox.ac.uk

Download Document from Source Website

File Size: 607,46 KB

Share Document on Facebook

Similar Documents

Process algebra and Markov processes The nature of synchronisation Equivalence relations Case study: active badges Summary  From Markov to Milner and back: Stochastic process algebras Jane Hillston School of Informatics

Process algebra and Markov processes The nature of synchronisation Equivalence relations Case study: active badges Summary From Markov to Milner and back: Stochastic process algebras Jane Hillston School of Informatics

DocID: 1xVg5 - View Document

Gaussian Stochastic ProcessesGaussian Stochastic Processes • Linear systems driven by IID noise • Evolution of mean and covariance • Example: mass-spring system

Gaussian Stochastic ProcessesGaussian Stochastic Processes • Linear systems driven by IID noise • Evolution of mean and covariance • Example: mass-spring system

DocID: 1uqvO - View Document

STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS MSRI Summer Graduate School July 7–18, A. A. Borovkov, Ergodicity and stability of stochastic processes, Wiley, Chichester, 1998, ISBNMRZbl 0

STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS MSRI Summer Graduate School July 7–18, A. A. Borovkov, Ergodicity and stability of stochastic processes, Wiley, Chichester, 1998, ISBNMRZbl 0

DocID: 1sRlG - View Document

Embedding machine learning in formal stochastic models of biological processes Jane Hillston School of Informatics, University of Edinburgh  29th October 2014

Embedding machine learning in formal stochastic models of biological processes Jane Hillston School of Informatics, University of Edinburgh 29th October 2014

DocID: 1sHGv - View Document

Stochastic Processes and their Applications–53  Self-collisions of superprocesses: renormalization and limit theorems Jay Rosen 1 Department of Mathematics, College of Staten Island, CUNY Staten Island, NY

Stochastic Processes and their Applications–53 Self-collisions of superprocesses: renormalization and limit theorems Jay Rosen 1 Department of Mathematics, College of Staten Island, CUNY Staten Island, NY

DocID: 1sGka - View Document