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2020 – today
- 2023
[j4]Niclas Eich, Martin Erdmann, Peter Fackeldey
, Benjamin Fischer, Dennis Noll, Yannik Rath:
Fast Columnar Physics Analyses of Terabyte-Scale LHC Data on a Cache-Aware Dask Cluster. Comput. Softw. Big Sci. 7(1): 3 (2023)- [c2]Astrid Schneidewind, Kilian Schwarz, Thomas Schörner, Bridget M. Murphy, Martin Erdmann:
Several Partners - Joint Effort: RDM Synergies in Large Scale Research. CoRDI 2023 - 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
- [b2]Martin Erdmann, Jonas Glombitza, Gregor Kasieczka, Uwe Klemradt:
Deep Learning for Physics Research. WorldScientific 2021, ISBN 9789811237454, pp. 1-340 - [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)
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) - [i2]Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Taylor Childers, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Javier M. Duarte, Martin Erdmann, Jonas Eschle, Amir Farbin, Matthew Feickert, Nuno Filipe Castro, Conor Fitzpatrick, Michele Floris, Alessandra Forti, Jordi Garra-Tico, Jochen Gemmler, Maria Girone, Paul Glaysher, Sergei Gleyzer, Vladimir V. Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Heinrich, Ben Hooberman, Johannes Junggeburth, Michael Kagan, Meghan Kane, Konstantin Kanishchev, Przemyslaw Karpinski, Zahari Kassabov, Gaurav Kaul, Dorian Kcira, Thomas Keck, Alexei Klimentov, Jim Kowalkowski, Luke Kreczko, Alexander Kurepin, Rob Kutschke, Valentin Kuznetsov, Nicolas Köhler, Igor Lakomov, Kevin Lannon, Mario Lassnig, Antonio Limosani, Gilles Louppe, Aashrita Mangu, Pere Mato, Narain Meenakshi, Helge Meinhard, Dario Menasce, Lorenzo Moneta, Seth Moortgat, Mark S. Neubauer, Harvey B. Newman, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel N. Perdue, Uzziel Perez, Attilio Picazio, Jim Pivarski, Harrison Prosper, Fernanda Psihas, Alexander Radovic, Ryan Reece, Aurelius Rinkevicius, Eduardo Rodrigues, Jamal Rorie, David Rousseau, Aaron Sauers, Steven Schramm, Ariel Schwartzman, Horst Severini, Paul Seyfert, Filip Siroky, Konstantin Skazytkin, Mike Sokoloff, Graeme Andrew Stewart, Bob Stienen, Ian Stockdale, Giles Chatham Strong, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Sofia Vallecorsa, Mauro Verzetti, Xavier Vilasís-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Omar Zapata:
Machine Learning in High Energy Physics Community White Paper. CoRR abs/1807.02876 (2018) - 2017
- [i1]Marcel Rieger, Martin Erdmann, Benjamin Fischer, Robert Fischer:
Design and Execution of make-like, distributed Analyses based on Spotify's Pipelining Package Luigi. CoRR abs/1706.00955 (2017)
2000 – 2009
- 2001
- [c1]Vinod Nair, Martin Erdmann, Shridhar Mubaraq Mishra, Juraj Povazanec, Amit Shaligram, Chun Feng Hu:
A single chip terminal solution for high-end telephone applications. CICC 2001: 417-420
1990 – 1999
- 1994
- [b1]Martin Erdmann:
Leistungsminimierende Transformationskodierung als Methode der Datenreduktion. University of Wuppertal, Germany, VDI-Verlag 1994, ISBN 978-3-18-332210-7, pp. 1-96
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