Today:
from the instrument to the data analysis.
Faustine Cantalloube (MPIA) on High-contrast imaging of exoplanets and circumstellar disks
15:00
Upcoming:
The Imprint of Cosmic Web Quenching on Galaxy Evolution
Nico Winkel
Thu, 11 Mar 2021, 11:00
MPIA travel analysis 2018-2020
Sustainability group
Thu, 11 Mar 2021, 11:00
MPIA business trip analysis 2018-2020
Jan Rybizki
Fri, 12 Mar 2021, 10:00

Statistics of Inverse Problems

Prof. Jan Johannes , Uni Heidelberg
Statistical ill-posed inverse problems are becoming increasingly important in a diverse range of disciplines, including geophysics, astronomy, medicine and economics. Roughly speaking, in all of these applications the observable signal g=Tf is a transformation of a functional parameter of interest f under a transformation T. Statistical inference on f based on an estimation of g which usually necessitates an inversion of T is thus called an inverse problem. Moreover, by ill-posed we mean that the transformation T is not stable, i.e., T has not a continuous inverse. In most applications, however, both the signal g and the inherent transformation T are not known in practice, although they can be estimated from the data. Consequently, a statistical inference has to take into account that a random noise is present in both the estimated signal and the estimated operator.
STRUCTURES Jour fixe
22 Jan 2021, 13:30
Institut für Theoretische Physik, Online

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