August 23, 2021 to October 7, 2021
Venue: OAC conference center, Kolymbari, Crete, Greece. Participation is possible also via internet.
Europe/Athens timezone

Machine Learning (CMS)

Aug 26, 2021, 6:40 PM
25m
Room 1

Room 1

Speaker

Savannah Jennifer Thais (Princeton University (US))

Description

In recent years, Machine Learning (ML) methods have become ubiquitous in High Energy Physics (HEP) research. This talk will explore current areas of ML for HEP research including event classification, object reconstruction, jet tagging, and accelerated ML inference for trigger environments. I will also discuss current opportunities and challenges in the ML for physics space and ways researchers can use these tools to advance science. Although this talk is focused on successful implementations of novel ML methods in the CMS experiment, the techniques and topics covered are relevant to a wide range of HEP experiments.

Details

Thais, Savannah Jennifer

Internet talk No
Is the speaker for that presentation defined? Yes
Name of experiment and experimental site CMS
Is this abstract from experiment? Yes

Primary author

Savannah Jennifer Thais (Princeton University (US))

Presentation materials

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