19 citations · 27 across the 6 of their papers we have counts for
5 papers · 1 filter
Weakly supervised machine learning for model-agnostic searches of new phenomena in the -ray sky
Michael Krämer, Silvia Manconi, Kathrin Nippel
The -ray sky, as observed by the Fermi Large Area Telescope, contains a significant number of unassociated sources that may point to new astrophysical populations or more exotic…
SECRET: Stochasticity Emulator for Cosmic Ray Electrons
Nikolas Frediani, Michael Krämer, Philipp Mertsch +1
The spectrum of cosmic-ray electrons depends sensitively on the history and spatial distribution of nearby sources. Given our limited observational handle on cosmic-ray sources, an…
Searching for dark matter subhalos in the Fermi-LAT catalog with Bayesian neural networks
Anja Butter, Michael Krämer, Silvia Manconi +1
About a third of the -ray sources detected by the Fermi Large Area Telescope (Fermi-LAT) remain unidentified, and some of these could be exotic objects such as dark matter subha…
EuCAPT White Paper: Opportunities and Challenges for Theoretical Astroparticle Physics in the Next Decade
R. Alves Batista, M. A. Amin, G. Barenboim +134
Astroparticle physics is undergoing a profound transformation, due to a series of extraordinary new results, such as the discovery of high-energy cosmic neutrinos with IceCube, the…
Constraining dark matter annihilation with cosmic ray antiprotons using neural networks
Felix Kahlhoefer, Michael Korsmeier, Michael Krämer +2
The interpretation of data from indirect detection experiments searching for dark matter annihilations requires computationally expensive simulations of cosmic-ray propagation. In…