ALPACA: modern algorithms in machine learning and data analysis: from medical physics to research with accelerators and in underground laboratories
Aula Renzo Leonardi
ECT*
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In the last two decades, the huge advances of artificial intelligence and machine learning (ML) algorithms have opened the door to incredible opportunities to the increased complexity experiments in physics and medical applications. The use of sophisticated models, once possible only with high commitment of resources and manpower, is now available off the shelf even to smaller groups and individuals. The ALPACA (modern ALgorithms in machine learning and data analysis: from medical Physics to research with ACcelerAtors and in underground laboratories) workshop aims to bring together researchers from different fields of fundamental and medical physics to share new ideas in development and deployment of algorithms, machine learning (ML) and data analysis techniques. The workshop will cover the physics-cases and the gains obtained with the use of ML, from the boosted decision tree and self-organizing maps used by the J-PET collaboration in Kraków, to the generative adversarial networks for event simulation at the LHC, passing to variational autoencoders for underground experiments. Hands-on sessions will also be organized.
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Alessio Lugnan
Andre Scaffidi
Andrea Barontini
Andrea Di Luca
Andrea Palladino
Bartosz Leszczynski
Daniel Lang
Fabio Catalano
Fabio Passi
Fabrizio Grosa
Fabrizio Napolitano
Federica Primavera
Florin Sirghi
Guido Sanguinetti
Ilya Auslender
Jakub Skowronski
Kamil Dulski
Kavya Valsan Eliyan
Laura Manduchi
Lorenzo Petrolli
Lucio Anderlini
Magdalena Skurzok
Manuel Micheloni
Marco Cristoforetti
Margherita Mele
Masar Al-muttairi
Oliver Schulz
Pietro Vischia
Raffaele Del Grande
Raffaello Potestio
Roberto Menichetti
Simone Manti
Takehiko Saito
Thomas Spieker
Tommaso Dorigo
William Korcari
Wojciech Krzemien