ALPACA: modern algorithms in machine learning and data analysis: from medical physics to research with accelerators and in underground laboratories

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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.