Optimising Geometric Deep Learning for Varied Reconstruction Tasks in High Granularity Calorimeters

In the recent years, high energy physics discoveries have been driven by the increasing of luminosity and/or detector granularity. This evolution gives access to bigger statistics and data samples, but can make it hard to process the detector outputs with current methods and algorithms. Graph Neural