Scientific Machine Learning Machine learning galore!

Machine learning galore will feature lab presentations by PIs as well as scientific talks by junior scientists.

Lab presentations: 
Klaus Maier-Hein • Florian Nieser • Wolfram Pernice

Science talks: 
• Saikat Roy (Maier-Hein lab): Flash over Function: A cautionary tale of trend-chasing from Medical AI 
• Daniel Schiller (Nieser-Plehn-Heneka labs): Repurposing Large Language Models for Cosmology 
• Frank Brückerhoff-Plückelmann (Pernice lab): Probabilistic Photonic Computing

Scientific Machine Learning is a joint initiative from STRUCTURES and IWR aimed at fostering interactions within and development of the local machine learning community. Its portal summarizes the many relevant events and news from across campus that would otherwise remain scattered across single institutions or fields.
The goals of the MLAI platform align with the STRUCTURES Cluster of Excellence's objective of driving research into the fundamental understanding of current and future machine learning, and with IWR’s aim to leverage machine learning to enable the solution of long-standing problems in the natural and life sciences, the engineering sciences, as well as the humanities.