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Machine Learning is a rapidly expanding field with a wide range ofapplications in science. In the field of physics, the Large Hadron Collider,the world's largest particle accelerator, utilizes Neural Networks for varioustasks, including flavour tagging. Flavour tagging is the process of identifyingthe flavour of the hadron that initiates a jet in a collision event, and it isan essential aspect of many Standard Model and Beyond the Standard Modelresearch. Graph Neural Networks are currently the primary machine-learning toolused for flavour tagging. Here, we present the AUTOGRAPH pipeline, a completelycustomizable tool designed with a user-friendly interface to provide easyaccess to the Graph Neural Networks algorithm used for flavour tagging.

Pipeline for performance evaluation of flavour tagging dedicated Graph Neural Network algorithms