2025-10-06 - 2025-10-10
Hier geht es zur AnmeldungTilman Plehn
Heidelberg University
Modern machine learning is not only revolutionizing our lives, it is also revolutionizing the way we do physics - or should do physics. I will present some more recent developments in Scientific ML, including learned uncertainties, representation learning, transformers and large language models in physics, and anomaly detection. They can be applied to a wide range of physics applications, from very large datasets and simulation-based inference in particle physics and astrophysics to low-count precision physics where optimal use of information is crucial.
