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Jonas Glombitza
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2020 – today
- 2022
- [j3]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:
Shared Data and Algorithms for Deep Learning in Fundamental Physics. Comput. Softw. Big Sci. 6(1) (2022) - 2021
- [b1]Martin Erdmann, Jonas Glombitza, Gregor Kasieczka, Uwe Klemradt:
Deep Learning for Physics Research. WorldScientific 2021, ISBN 9789811237454, pp. 1-340 - [i1]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:
Shared Data and Algorithms for Deep Learning in Fundamental Physics. CoRR abs/2107.00656 (2021)
2010 – 2019
- 2019
- [j2]Martin Erdmann, Jonas Glombitza, Thorben Quast:
Precise Simulation of Electromagnetic Calorimeter Showers Using a Wasserstein Generative Adversarial Network. Comput. Softw. Big Sci. 3(1) (2019) - 2018
- [j1]Martin Erdmann, Lukas Geiger, Jonas Glombitza, David Schmidt:
Generating and Refining Particle Detector Simulations Using the Wasserstein Distance in Adversarial Networks. Comput. Softw. Big Sci. 2(1) (2018)
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