12.–14. Nov. 2025
SoN
Europe/Berlin Zeitzone

Representation learning for LHC physics

14.11.2025, 11:00
30m
SoN

SoN

Talk Plenary

Sprecher

Tilman Plehn (Heidelberg University)

Beschreibung

LHC physics, just like our lives, is being transformed by modern machine learning. This is motivated by the vast data stream and the role of simulations encoding fundamental physics knowledge. The scientific AI program around the LHC comes with unique advantages: we understand the feature space and scattering dynamics in terms of fundamental symmetries and quantum field theory; we have full control over uncertainties; and ML tasks are parts of an advanced statistical analysis framework. I will show how these strengths allow us develop and establish exciting concepts in representation learning, targeting requirements like accuracy, precision, and control.

Präsentationsmaterialien