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Matthew Feickert
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2020 – today
- 2024
- [i6]Marco Donadoni, Matthew Feickert, Lukas Heinrich, Yang Liu, Audrius Mecionis, Vladyslav Moisieienkov, Tibor Simko, Giordon Stark, Marco Vidal García:
Scalable ATLAS pMSSM computational workflows using containerised REANA reusable analysis platform. CoRR abs/2403.03494 (2024) - 2022
- [i5]Gabriele Benelli, Thomas Y. Chen, Javier M. Duarte, Matthew Feickert, Matthew J. Graham, Lindsey Gray, Dan Hackett, Philip C. Harris, Shih-Chieh Hsu, Gregor Kasieczka, Elham E Khoda, Matthias Komm, Mia Liu, Mark S. Neubauer, Scarlet Norberg, Alexx Perloff, Marcel Rieger, Claire Savard, Kazuhiro Terao, Savannah Thais, Avik Roy, Jean-Roch Vlimant, Grigorios Chachamis:
Data Science and Machine Learning in Education. CoRR abs/2207.09060 (2022) - 2021
- [j2]Sudhir Malik, Samuel Meehan, Kilian Lieret, Meirin Oan Evans, Michel Hernández Villanueva, Daniel S. Katz, Graeme A. Stewart, Peter Elmer, Sizar Aziz, Matthew Bellis, Riccardo Maria Bianchi, Gianluca Bianco, Johan Sebastian Bonilla, Angela Burger, Jackson Burzynski, David Chamont, Matthew Feickert, Philipp Gadow, Bernhard Manfred Gruber, Daniel Guest, Stephan Hageboeck, Lukas Heinrich, Maximilian M. Horzela, Marc Huwiler, Clemens Lange, Konstantin Lehmann, Ke Li, Devdatta Majumder, Judita Mamuzic, Kevin Nelson, Robin Newhouse, Emery Nibigira, Scarlet Norberg, Arturo Sánchez Pineda, Mason Proffitt, Brendan Regnery, Amber Roepe, Stefan Roiser, Henry Schreiner, Oksana Shadura, Giordon Stark, Stephen Nicholas Swatman, Savannah Thais, Andrea Valassi, Stefan Wunsch, David Yakobovitch, Siqi Yuan:
Software Training in HEP. Comput. Softw. Big Sci. 5(1) (2021) - [j1]Lukas Heinrich, Matthew Feickert, Giordon Stark, Kyle Cranmer:
pyhf: pure-Python implementation of HistFactory statistical models. J. Open Source Softw. 6(58): 2823 (2021) - [i4]Matthew Feickert, Benjamin Nachman:
A Living Review of Machine Learning for Particle Physics. CoRR abs/2102.02770 (2021) - [i3]Matthew Feickert, Lukas Heinrich, Giordon Stark, Ben Galewsky:
Distributed statistical inference with pyhf enabled through funcX. CoRR abs/2103.02182 (2021) - 2020
- [i2]Daniel S. Katz, Sudhir Malik, Mark S. Neubauer, Graeme Andrew Stewart, Kétévi A. Assamagan, Erin A. Becker, Neil P. Chue Hong, Ian A. Cosden, Samuel Meehan, Edward J. W. Moyse, Adrian M. Price-Whelan, Elizabeth Sexton-Kennedy, Meirin Oan Evans, Matthew Feickert, Clemens Lange, Kilian Lieret, Rob Quick, Arturo Sánchez Pineda, Christopher D. Tunnell:
Software Sustainability & High Energy Physics. CoRR abs/2010.05102 (2020)
2010 – 2019
- 2018
- [i1]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)
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