3 papers
hep-ph2021
Autoencoders for unsupervised anomaly detection in high energy physics
Thorben Finke, Michael Krämer, Alessandro Morandini +2
Autoencoders are widely used in machine learning applications, in particular for anomaly detection. Hence, they have been introduced in high energy physics as a promising tool for…
astro-ph.HE2020
Classification of Fermi-LAT sources with deep learning using energy and time spectra
Thorben Finke, Michael Krämer, Silvia Manconi
Despite the growing number of gamma-ray sources detected by Fermi-LAT, about one third of the sources in each survey remains of uncertain type. We present a new deep neural network…
hep-ph2020
Casting a graph net to catch dark showers
Elias Bernreuther, Thorben Finke, Felix Kahlhoefer +2
Strongly interacting dark sectors predict novel LHC signatures such as semi-visible jets resulting from dark showers that contain both stable and unstable dark mesons. Distinguishi…