Nov 6 – 10, 2023
Europe/Zurich timezone

Machine learning has become a hot topic in particle physics over the past several years. In particular, there has been a lot of progress in the areas of particle and event identification, reconstruction, generative models, anomaly detection and more. In this conference, we will discuss current progress in these areas, focusing on new breakthrough ideas and existing challenges. 

The ML4Jets workshop will be open to the full community and will include LHC experiments as well as theorists and phenomenologists interested in this topic. We explicitly welcome contributions and participation from method scientists as well as adjacent scientific fields such as astronomy, astrophysics, astroparticle physics, hadron- and nuclear physics and other domains facing similar challenges.

This year's conference is organised jointly by DESY and Universität Hamburg and hosted at the DESY campus. It follows conferences in 201720182020, 2021, and 2022.

In-person registration and abstract submission are closed. Remote registration is possible until the end of the workshop.

The workshop will be organised in a hybrid format (with a Zoom connection option). We expect speakers to attend in-person.

Registration for both in-person and Zoom-participation will be free of charge and (at the minimum) include coffee-breaks for in-person participants. We are looking into an opt-in dinner and announce details and potential extra costs closer to the event.

Join the ML4Jets Slack Channel for discussions. 

Local Organizing Committee:
Freya Blekman (DESY & Universität Hamburg)
Andrea Bremer (Universität Hamburg)
Frank Gaede (DESY)
Gregor Kasieczka (Universität Hamburg, chair)
Andreas Hinzmann (DESY)
Matthias Schröder (Universität Hamburg)

International Advisory Committee:
Florencia Canelli (University of Zurich)
Kyle Cranmer (NYU)
Vava Gligorov (LPNHE)
Gian Michele Innocenti (CERN)
Ben Nachman (LBNL)
Mihoko Nojiri (KEK)
Maurizio Pierini (CERN)
Tilman Plehn (Heidelberg)
David Shih (Rutgers)
Jesse Thaler (MIT)
Sofia Vallescorsa (CERN)




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