Rhode, WolfgangHünnefeld, Mirco2023-11-302023-11-302023http://hdl.handle.net/2003/42209http://dx.doi.org/10.17877/DE290R-24043With the discovery of the astrophysical neutrino flux by IceCube in 2013, the foundation for neutrino astronomy was established. In subsequent years, the first point-like neutrino source candidates, a flaring blazar known as TXS 0506+056 and the active galaxy NGC 1068, emerged. Now, in this work, a new milestone in the rising field of neutrino astronomy is presented: the first observation of high-energy neutrinos from our own Galaxy — the Milky Way. A search for Galactic neutrino emission is performed on 10 years of IceCube data, rejecting the background-only hypothesis at the 4.5σ significance level. The observed Galactic neutrino flux, believed to originate from diffuse interactions of cosmic rays, possibly in addition to contributions from unresolved point-like sources, may explain up to 10% of the astrophysical neutrino flux previously measured by IceCube. This observation is enabled by novel tools based on deep learning, developed in this dissertation. In comparison to prior IceCube analyses, the sensitivity is improved by a factor up to four, due to improved event reconstructions and an increased effective area by over an order of magnitude. These tools not only lead to the most sensitive neutrino dataset to date in the Southern Sky, but they also enable a wide variety of future applications and analyses that were previously unattainable.enNeutrinoAstronomyAstroparticle physicsGalactic planeMilky WayMachine learningDeep learning530TextNeutrinoNeutrinoastronomieAstrophysikGalaxieMaschinelles LernenDeep learning