Speaker
Description
Physicists aim to reconstruct the distribution of physical quantities from the vast amounts of data collected by telescopes, as a means to better understand the physical processes of the Universe. This
reconstruction involves solving an inverse problem, specifically the Fredholm integral equation highlighted in the overview of this workshop. Methods for finding such a solution are not only studied in physics but also in computer science and machine learning research. In these fields, the cognitive interest lies not in the physical implications of the reconstructed distribution but in the properties and reliability of the reconstruction methods themselves. For instance: Can a given method guarantee a certain level of accuracy? What conditions must be met to ensure such guarantees? This talk invites participants to discuss the epistemological issues related to these machine learning questions.
