The workshop takes place at the TU Dortmund, Lamarr Institute, and can be attended online via Zoom. It is part of the interdisciplinary research project “Data, Theories, and Scientific Explanation: The Case of Astroparticle Physics” funded by the DFG (German Research Foundation). It will bring together philosophers of science and colleagues from astroparticle physics, computer science, and statistics. It will focus on the way in which machine learning models manage to extract significant data from data sets that contain a huge background of irrelevant data. Current methods of statistical data analysis base the extraction of the significant data on probabilistic quality standards for representative signatures and employ machine learning models to extract the relevant data subsamples.
Invited Speakers: Pierre-Hugues Beauchemin (Tufts University), Silvia De Bianchi (Milano), Koray Karaca (Ankara), Mahdi Khalili (Bern), Michael Schmelling (Heidelberg), Dinah Pfau (München), Kent W. Staley (Saint Louis University), Michael Stöltzner (South Carolina)
For further information and the zoom-link, see https://events.lamarr-institute.org/event/441