The workshop will be held on 9-13th May 2022
Please note that the event is foreseen to be held in a hybrid form, with a large in-person attendance. We don't anticipate any issue with that, buf of course in case of national (COVID) emergency we may have to move it back to online-only form.
You will have to arrange for your own accommodation, either in the CERN Hostel (https://edh.cern.ch/Hostel/, subject to room availability) or in nearby hotels.
Please make sure to be registered to firstname.lastname@example.org CERN egroup, to be informed of any unforeseen circumstance.
This is the fifth annual workshop of the LPCC inter-experimental machine learning working group at CERN. It will take place at CERN with remote participation made possible.
The structure is the following :
- Monday 9th May: Tutorials (starting at 13:00 GVA)
- Tuesday 10th May : Plenary (all day long)
- Wednesday 11th May-Friday 13th May: workshop sessions (all day long)
The following plenary speakers are foreseen (re-confirmation after rescheduling in progress):
- Coline Devin (Deepmind Robotics)
- Laurent Daudet (LightOn)
- Anna Goldie (Google Brain)
- Alex Gramfort (INRIA)
- Tommaso Dorigo (U Padova)
- Nils Thuerey (TUM)
- Sofia Vallecorsa (CERN)
- Christoph Weniger (GRAPPA, Amsterdam)
The bulk of the workshop will be be built from contributed talks, (abstract submission is closed, selection being done). For the contributed talks, the following Tracks have been defined:
- ML for object identification and reconstruction
- ML for analysis : event classification, statistical analysis and inference, including anomaly detection
- ML for simulation and surrogate model : Application of Machine Learning to simulation or other cases where it is deemed to replace an existing complex model
- Fast ML : Application of Machine Learning to DAQ/Trigger/Real Time Analysis
- ML infrastructure : Hardware and software for Machine Learning
- ML training, courses, tutorial, open datasets and challenges
- ML for astroparticle
- ML for phenomenology and theory
- ML for particle accelerators