Seminarium Fizyki Wielkich Energii

Machine Learning plays an increasingly central role in the CMS experiment, supporting improvements across detector operations, event reconstruction, and physics analysis. This seminar provides an overview of how modern ML techniques are being applied within CMS, with examples ranging from enhanced detector-level reconstruction to likelihood-free inference methods and the use of normalizing flows for calibration tasks. These developments highlight the growing impact of machine learning applications for precise measurements and future discoveries at the LHC.