|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