The event will take place live at CERN under the conditions that CERN regulations allow it and travel in most part of Europe has resumed. In any case remote participation will be possible. Please make sure to be registered to firstname.lastname@example.org CERN egroup, to be informed about further developments.
This is the fourth annual workshop of the LPCC inter-experimental machine learning working group. As 2019 edition, it will take place at CERN, and everyone interested in ML for HEP is invited! Remote participation will be supported via the Vidyo and CERN webcast services.
The following structure is anticipated:
- Monday 19th Oct : hands-on tutorials : 1/2 day hls4ml, 1/2 day Graph Neural Networks by Deepmind
- Tuesday 20th Oct : morning : invited talks (confirmed speakers Peter Battaglia (DeepMind), Ulrich Koethe (U Heidelberg), Amir Farbin (UTA), Kazuhiro Terao (SLAC) , afternoon industry session
- Wednesday 21st/Thursday 22nd : contributed talks
Abstract submission is now opened until Friday 4th September.
For the contributed talks, the following (non exclusive) Tracks have been defined:
- ML for data reduction : Application of Machine Learning to data reduction, reconstruction, building/tagging of intermediate object
- ML for analysis : Application of Machine Learning to analysis, event classification and fundamental parameters inference
- 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 algorithms : Machine Learning development across applications
- ML infrastructure : Hardware and software for Machine Learning
- ML training, courses and tutorials
- ML open datasets and challenges
- ML for astroparticle
- ML for experimental particle physics
- ML for phenomenology and theory
- ML for particle accelerators