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SUMMARY:Prof. Carola-Bibiane Schönlieb: Inverse Problems in Imaging: From
  Differential Equations to Deep Learning
DTSTART:20220512T170000
DTEND:20220512T183000
DTSTAMP:20260501T224401Z
UID:4754c8a4f7b2cccfafd8bcda0178a39c3276b5fdc53f3f64b20c54d8
CATEGORIES:Conferences - Seminars
DESCRIPTION:Abstract. In the last couple of years the processing and analy
 sis of imaging data has undergone a significant paradigm shift\, from know
 ledge driven approaches that derive imaging models from first principles t
 o purely data driven approaches that derive models from data. In this talk
  I will discuss image processing methods that operate at the interface of 
 these paradigms and feature both a knowledge driven (mathematical modellin
 g) and a data driven (machine learning) component. Mathematical modelling 
 is useful in the presence of prior information about the imaging data and 
 relevant features of interest\, for narrowing down the search space\, for 
 highly generalizable methods with solutions that come with theoretical sol
 ution guarantees. Machine learning on the other hand is a powerful tool fo
 r customising image processing methods to individual data sets. Their comb
 ination is the topic of this talk\, furnished with examples for image clas
 sification under minimal supervision with an application to chest x-rays\,
  tomographic image reconstruction with learned priors and fast spatio-temp
 oral MRI.\n\nBiography. Carola-Bibiane Schönlieb graduated from the Insti
 tute for Mathematics\, University of Salzburg (Austria) in 2004. From 2004
  to 2005 she held a teaching position in Salzburg. She received her PhD de
 gree from the University of Cambridge (UK) in 2009. After one year of post
 doctoral activity at the University of Göttingen (Germany)\, she became a
  Lecturer at Cambridge in 2010\, promoted to Reader in 2015 and promoted t
 o Professor in 2018. Since 2011 she is a fellow of Jesus College Cambridge
  and since 2016 a fellow of the Alan Turing Institute\, London. She curren
 tly is Professor of Applied Mathematics at the University of Cambridge\, w
 here she is head of the Cambridge Image Analysis group and co-Director of 
 the EPSRC Cambridge Mathematics of Information in Healthcare Hub. Her curr
 ent research interests focus on variational methods\, partial differential
  equations and machine learning for image analysis\, image processing and 
 inverse imaging problems.
LOCATION:BM 5202 https://plan.epfl.ch/?room==BM%205202 https://epfl.zoom.u
 s/j/69613186417
STATUS:CONFIRMED
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