Speaker
Description
Over the last decade, AI-algorithms have become a standard tool for data analysis in astroparticle physics. While these efforts were pioneered by the use of ensemble methods for event selection in IceCube, the capabilities of AI in the context of neutrino astronomy have been exemplified by the detection of neutrinos from the Milky Way (also by the IceCube collaboration). This detection was enabled by the use of deep neural networks, which allow for a more precise reconstruction of the neutrino trajectory and a more sophisticated event selection. At the same time efforts are underway to also leverage the capabilities of GNNs and transformer models for the event reconstruction in neutrino astronomy. This poster will provide an overview over the state-of-the-art with respect to the utilization of AI in astroparticle physics, with a dedicated focus on neutrino astronomy.
