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ORCIDLukas Heinrich
Person information
- affiliation: TU Munich, Germany
- affiliation (former): CERN, Geneva, Switzerland
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2020 – today
- 2023
[i10]Francesco Armando Di Bello, Anton Charkin-Gorbulin, Kyle Cranmer, Etienne Dreyer, Sanmay Ganguly, Eilam Gross, Lukas Heinrich, Lorenzo Santi, Marumi Kado, Nilotpal Kakati, Patrick Rieck, Matteo Tusoni:
Configurable calorimeter simulation for AI applications. CoRR abs/2303.02101 (2023)- 2022
- [i9]Lukas Heinrich, Michael Kagan:
Differentiable Matrix Elements with MadJax. CoRR abs/2203.00057 (2022) - [i8]Nathan Simpson, Lukas Heinrich:
neos: End-to-End-Optimised Summary Statistics for High Energy Physics. CoRR abs/2203.05570 (2022) - [i7]E. A. Huerta, Ben Blaiszik, L. Catherine Brinson, Kristofer E. Bouchard, Daniel Diaz, Caterina Doglioni, Javier M. Duarte, Murali Emani, Ian T. Foster, Geoffrey C. Fox, Philip C. Harris, Lukas Heinrich, Shantenu Jha
, Daniel S. Katz, Volodymyr V. Kindratenko, Christine R. Kirkpatrick, Kati Lassila-Perini, Ravi K. Madduri, Mark S. Neubauer, Fotis E. Psomopoulos, Avik Roy, Oliver Rübel, Zhizhen Zhao, Ruike Zhu:
FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. CoRR abs/2210.08973 (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]Tibor Simko, Lukas Alexander Heinrich, Clemens Lange, Adelina Eleonora Lintuluoto, Danika Marina MacDonell, Audrius Mecionis, Diego Rodríguez Rodríguez, Parth Shandilya, Marco Vidal García:
Scalable Declarative HEP Analysis Workflows for Containerised Compute Clouds. Frontiers Big Data 4: 661501 (2021) - [d1]Lukas Heinrich, Matthew Feickert, Giordon Stark, Kyle Cranmer:
pyhf: pure-Python implementation of HistFactory statistical models. J. Open Source Softw. 6(58): 2823 (2021) - [i6]Matthew Feickert, Lukas Heinrich, Giordon Stark, Ben Galewsky:
Distributed statistical inference with pyhf enabled through funcX. CoRR abs/2103.02182 (2021)
2010 – 2019
- 2019
- [c3]Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood:
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. NeurIPS 2019: 5460-5473 - [c2]Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood:
Etalumis: bringing probabilistic programming to scientific simulators at scale. SC 2019: 29:1-29:24 - [i5]Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood:
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale. CoRR abs/1907.03382 (2019) - 2018
- [c1]Tibor Simko, Kyle Cranmer, Michael R. Crusoe, Lukas Heinrich, Anton Khodak, Dinos Kousidis, Diego Rodriguez:
Search for Computational Workflow Synergies in Reproducible Research Data Analyses in Particle Physics and Life Sciences. eScience 2018: 403-404 - [i4]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) - [i3]Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank D. Wood:
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. CoRR abs/1807.07706 (2018) - 2017
- [i2]Eamonn Maguire, Lukas Heinrich, Graeme Watt:
HEPData: a repository for high energy physics data. CoRR abs/1704.05473 (2017) - [i1]Mario Lezcano Casado, Atilim Gunes Baydin, David Martínez-Rubio, Tuan Anh Le, Frank D. Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji, Prabhat:
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators. CoRR abs/1712.07901 (2017)
Coauthor Index
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