Data and MC represent different domains. Supervised learning in MC needs to be transferred to the real data domain and MC mismodelling can reduce the performance of the transferred models. In this work we are implementing the Domain Adversarial Neural Network (DANN) concept to the standard Graph Neural Network (GNN) classification and regression tasks in the KM3NeT/ORCA experiment. We will present the current status and prospects for the project.
Joao Coelho (APC / CNRS)