Training School on Data Assimilation, Inverse Problems and Machine Learning

May 8-10, 2019

Program
 

Wednesday, May 8, 2019
08:30 - 09:00
Registration (5345) and Coffee & Croissants


09:00 - 10:30
Andrew M. Stuart
(California Institute of Technology)
Inverse Problems generally (optimization and Bayesian) will whole story exemplified through semi-supervised graph based learning - Part I
10:30 - 11:15
Coffee break
11:15 - 12:45
Eldad Haber
(The University of British Columbia)
DNNs/supervised learning as an inverse problem - Part I
12:45 - 14:15
Lunch break
14:15 - 15:45
Andrew M. Stuart
(California Institute of Technology)
Inverse Problems generally (optimization and Bayesian) will whole story exemplified through semi-supervised graph based learning - Part II
15:45 - 16:15
Coffee

 

Thursday, May 9, 2019
08:30 - 09:00
Coffee & Croissants


09:00 - 10:30
Sebastian Reich
(Universität Postdam)
Data Assimilation - Part I
Script
10:30 - 11:15
Coffee break
11:15 - 12:45
Andrew M. Stuart
(California Institute of Technology)
Inverse Problems generally (optimization and Bayesian) will whole story exemplified through semi-supervised graph based learning - Part III
12:45 - 14:15
Lunch break
14:15 - 15:45
Eldad Haber
(The University of British Columbia)
DNNs/supervised learning as an inverse problem - Part II
15:45
Poster Sesssion and Coffee

 

Friday, May 10, 2019
08:30 - 09:00
Coffee & Croissants


09:00 - 10:30
Sebastian Reich
(Universität Postdam)
Data Assimilation - Part II
Script
10:30 - 11:15
Coffee break
11:15 - 12:45
Eldad Haber
(The University of British Columbia)
DNNs/supervised learning as an inverse problem - Part III
12:45 - 14:15
Lunch break
14:15 - 15:45
Sebastian Reich
(Universität Postdam)
Data Assimilation - Part III
Script
15:45 - 16:15
Coffee

Last modified : Wednesday, May 1, 2019 17:07