Videos available on the webcast of the workshop
General Information
The workshop will take place in person in Paris at APC from Monday 26 Sep 10:30 am to Wednesday 28 Sep 4pm. A social reception will take place Tuesday night.
Directions to reach APC are given at the bottom of this page along with a downloadable EPUB booklet with practical information about the event and where to eat around APC.
Introduction
Machine Learning is now potentially impacting many aspects of particle physics, nuclear physics and astroparticle physics.
This workshop covers current developments with Machine Learning at IN2P3 and CEA-IRFU.
The call for contribution is not limited to finished work, work in progress or even Expression of Interest are very welcome. (Since this is a national workshop, experimental contributions by students need not be approved by the collaboration, but please refer to the experiment national contact for the exact rules).
The call for contributions is now closed.
Tracks
- 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 phenomenology and theory (only if does not fit in Tracks above)
- ML for particle accelerators (only if does not fit in Tracks above)
- Others
Mailing list
Please make sure you are subscribed to MACHINE-LEARNING-L@in2p3.fr on IN2P3 listserv to keep up to date with ML.
Organisation : Alexandre Boucaud (APC/IN2P3), Valérie Gautard (CEA/IRFU), David Rousseau (IJCLab/IN2P3)
