What's on in Computing Science?
Date: Thursday, 22 January, 2009
Sir Alwyn Williams Building, 422 Seminar Room
Approximate inference in continuous time discrete and hybrid stochastic systems
Guido Sanguinetti (University of Sheffield)
In this talk I will present some results on inference for continuous time stochastic processes. The type of process we will consider is the Markov Jump process (MJP), where the state of the system (a multi-dimensional vector with integer entries) evolves in continuous time with Markovian dynamics. This type of system is frequently used in modelling chemical reactions at low count numbers, or in ecological systems. In the first part of the process I'll introduce a variational framework for inference from noisy observations of a MJP. In the second part, I will present some more recent work on hybrid systems where a latent MJP drives the dynamics of continuous observed variables.
Contact: Dr Rónán Daly (email@example.com)
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