PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Approximate parameter inference in a stochastic reaction-diffusion model
Andreas Ruttor and Manfred Opper
AISTATS 2010 2010.

Abstract

We present an approximate inference approach to parameter estimation in a spatio - temporal stochastic process of the reaction diffusion type. The continuous space limit of an inference method for Markov jump processes leads to an approximation which is related to a spatial Gaussian process. An efficient solution in feature space using a Fourier basis is applied to inference on simulational data.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
ID Code:8043
Deposited By:Manfred Opper
Deposited On:17 March 2011