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ORCIDTilman Plehn
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2020 – today
- 2024
[i8]Nathan Huetsch, Javier Mariño Villadamigo, Alexander Shmakov, Sascha Diefenbacher, Vinicius Mikuni, Theo Heimel, Michael James Fenton, Kevin Greif, Benjamin Nachman, Daniel Whiteson, Anja Butter, Tilman Plehn:
The Landscape of Unfolding with Machine Learning. CoRR abs/2404.18807 (2024)- [i7]Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer:
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics. CoRR abs/2405.14806 (2024) - 2023
- [i6]Barry M. Dillon, Luigi Favaro, Friedrich Feiden, Tanmoy Modak, Tilman Plehn:
Anomalies, Representations, and Self-Supervision. CoRR abs/2301.04660 (2023) - 2022
- [j1]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
- [i5]Marco Bellagente, Manuel Haußmann, Michel Luchmann, Tilman Plehn:
Understanding Event-Generation Networks via Uncertainties. CoRR abs/2104.04543 (2021) - [i4]Barry M. Dillon, Tilman Plehn, Christof Sauer, Peter Sorrenson:
Better Latent Spaces for Better Autoencoders. CoRR abs/2104.08291 (2021) - [i3]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) - [i2]Anja Butter, Theo Heimel, Sander Hummerich, Tobias Krebs, Tilman Plehn, Armand Rousselot, Sophia Vent:
Generative Networks for Precision Enthusiasts. CoRR abs/2110.13632 (2021)
2010 – 2019
- 2019
- [i1]Marco Bellagente, Anja Butter, Gregor Kasieczka, Tilman Plehn, Ramon Winterhalder:
How to GAN away Detector Effects. CoRR abs/1912.00477 (2019)
Coauthor Index
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