The Inter-experimental LHC Machine Learning (IML) Working Group is focused on the development of modern state-of-the art machine learning methods, techniques and practices for high-energy physics problems. We provide solutions, software and training beneficial to LHC and other high-energy physics experiments as well as a forum where on-going work and relevant issues are discussed by the community.
We meet regularly and focus on best techniques and practices, solutions to common problems, and ways to tackle open challenges. We additionally provide an interface with the machine-learning community at large, both benefiting from outside progress in HEP, as well as exporting ML solutions developed in HEP to the outside.
Who we are
There are a large number of contributors from many different institutions and laboratories, spanning all the LHC and other HEP experiments, as well as experts outside of these communities and with the participation of the SFT team at CERN. The activities of the group are coordinated by Sergei Gleyzer, Steven Schramm, Michele Floris and Paul Seyfert.
IML WG Coordinators: