Approximate parameter inference in a stochastic reaction-diffusion model

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.

• Type: Journal
• Year: 2010
• Where: JMLR
• Authors: Andreas Ruttor, Manfred Opper
• Keywords: Approximate Inference Approach, Inference, JMLR 2010, Spatio-temporal Stochastic Process