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DTSTART;TZID=Europe/Ljubljana:20240627T140000
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SUMMARY:Manuel Szewc: Modeling Hadronization with Machine Learning
DESCRIPTION:A fundamental part of event generation\, hadronization is currently simulated with the help of fine-tuned empirical models. Motivated by the difficulties of these models\, in this talk I’ll present MLHAD: a proposed alternative where the empirical model is replaced by a surrogate Machine Learning-based model to be ultimately data-trainable. I’ll detail the current stage of development and discuss challenges and possible ways forward.\nhttps://indico.ijs.si/event/2088/
URL:https://web-f1.ijs.si/event/manuel-szewc/
LOCATION:https://zoom.us/j/3601731049?pwd=bVNQRjUxU2ExZ0cveWcxYXNUUGdjZz09 (F1 tea room)
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