1 code implementation • 1 Jul 2021 • Lisa Benato, Erik Buhmann, Martin Erdmann, Peter Fackeldey, Jonas Glombitza, Nikolai Hartmann, Gregor Kasieczka, William Korcari, Thomas Kuhr, Jan Steinheimer, Horst Stöcker, Tilman Plehn, Kai Zhou
We introduce a Python package that provides simply and unified access to a collection of datasets from fundamental physics research - including particle physics, astroparticle physics, and hadron- and nuclear physics - for supervised machine learning studies.
1 code implementation • 5 Jul 2018 • Martin Erdmann, Jonas Glombitza, Thorben Quast
The generator is constraint during the training such that the generated showers show the expected dependency on the initial energy and the impact position.
Instrumentation and Detectors
no code implementations • 9 Feb 2018 • Martin Erdmann, Lukas Geiger, Jonas Glombitza, David Schmidt
We use adversarial network architectures together with the Wasserstein distance to generate or refine simulated detector data.
Instrumentation and Methods for Astrophysics High Energy Physics - Experiment