Flow-based Bayesian Estimation of Nonlinear Differential Equations for Modeling Biological Network

author: Nicolas Brunel, IBISC laboratory, Université Evry Val d'Essonne
published: Oct. 14, 2010,   recorded: September 2010,   views: 3268
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography

Description

We consider the problem of estimating parameters and unobserved trajectories in nonlinear ordinary differential equations (ODEs) from noisy and partially observed data. We focus on a class of state-space models defined from the integration of the differential equation in the evolution equation. Within a Bayesian framework, we derive a non-sequential estimation procedure that infers the parameters and the initial condition of the ODE, taking into account that both are required to fully characterize the solution of the ODE. This point of view, new in the context of state-space models, modifies the learning problem. To evaluate the relevance of this approach, we use an Adaptive Importance Sampling in a population Monte Carlo scheme to approximate the posterior probability distribution. We compare this approach to recursive estimation via Unscented Kalman Filtering on two reverse-modeling problems in systems biology. On both problems, our method improves on classical smoothing methods used in state space models for the estimation of unobserved trajectories.

See Also:

Download slides icon Download slides: prib2010_brunel_fben_01.pdf (531.2 KB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: