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SUMMARY:Parameter inference\, model error and the goals of calibration - D
 aniel Williamson (University of Exeter)
DTSTART:20180411T103000Z
DTEND:20180411T110000Z
UID:TALK103651@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:I have some data\, a mathematical model describing a process i
 n the real world that produced that data and I would like to learn somethi
 ng about the real world. We would typically formulate this as an inverse p
 roblem and apply our favourite techniques for solving it (e.g. Bayesian ca
 libration or history matching)\, ultimately providing inference for those 
 parameters in our mathematical model that are consistent with the data. Do
 es this make sense? In this talk\, I will use climate science as a lens th
 rough which we can look at how mathematical models are viewed and treated 
 by the scientific community\, and consider UQ approaches to inverse proble
 ms and how they might fit and ask whether it matters if they don&#39\;t.
LOCATION:Seminar Room 1\, Newton Institute
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