Regensburg 2025 – scientific programme

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TUT: Tutorien

TUT 1: Hands-on Tutorial: AI Fundamentals for Research (joint session BP/TUT/DY/AKPIK)

TUT 1.2: Tutorial

Sunday, March 16, 2025, 16:40–17:25, H2

Hands-On Session 1 -- Function Approximation — •Jan Bürger¹, Janine Graser², Robin Msiska^2,3, and Arash Rahimi-Iman⁴ — ¹ErUM-Data-Hub, RWTH Aachen University, Aachen, Germany — ²Faculty of Physics and Center for Nanointegration Duisburg-Essen (CENIDE), University of Duisburg-Essen, Duisburg, Germany — ³Department of Solid State Sciences, Ghent University, Ghent, Belgium — ⁴I. Physikalisches Institut and Center for Materials Research, Justus-Liebig-University Gießen, Gießen, Germany

In the first half of the interactive session, participants will work with Jupyter Notebooks to explore practical applications of machine learning. They will train simple neural networks to predict a mathematical function, gaining hands-on experience in tuning key parameters. Since neural networks can typically be considered universal function approximators, this concept is effectively illustrated using a one-dimensional function, making it easy to visualize and understand.

Keywords: AI; hands-on