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Mathematics Colloquium

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Date:  Tuesday, March 25, 2014

Title:  Computing with Uncertainty

Abstract:  There are many problems in science and engineering where one needs to estimate the solution of uncertain equations with uncertain or incomplete data. I will present examples, in particular, the estimation of model parameters from noisy data (as in the modeling of diffusion), inference from stochastic differential equations supplemented by a stream of random data (as in economic or weather prediction), and the solution of differential equations with random data (as in uncertainty quantification and statistical mechanics). I will discuss why predictions fail and the conditions under which such problems can be solved in principle and in practice. I will not assume any previous familiarity with this class of problems.


Speaker:  Alexandre Chorin
Institution:  University of California, Berkeley

 

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