BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//University of Utah Math Department//Variational Data Assimilation and Regularization for Ill-posed Problems: A Common Framework//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Variational Data Assimilation and Regularization for Ill-posed Problems: A Common Framework
X-WR-CALDESC:Variational Data Assimilation and Regularization for Ill-posed Problems: A Common Framework at University of Utah Mathematics Department
X-WR-TIMEZONE:America/Denver
BEGIN:VEVENT
UID:20240411T160000-jodi-mead@math.utah.edu
DTSTART;TZID=America/Denver:20240411T160000
DTEND;TZID=America/Denver:20240411T170000
DTSTAMP:20260922T150858Z
SUMMARY:Variational Data Assimilation and Regularization for Ill-posed Problems: A Common Framework
DESCRIPTION:Speaker: Jodi Mead\, Boise State University\n\nData assimilation and inverse methods for ill-posed problems find optimal estimates of states or parameters. Methods for both combine observations with a model, which here we assume is a partial differential equation (PDE). Finding a compromise between observations and model is challenging because …

LOCATION:JWB 335

URL:https://www.math.utah.edu/research/colloquia/2024-04-11-jodi-mead/
END:VEVENT
END:VCALENDAR