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Tobias Golling
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2020 – today
- 2023
- [j1]Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather M. Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau
, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant:
The Tracking Machine Learning Challenge: Throughput Phase. Comput. Softw. Big Sci. 7(1): 1 (2023) - [i12]Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant, John Andrew Raine, Knut Zoch, Tobias Golling:
PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics. CoRR abs/2303.05376 (2023) - 2022
- [i11]Atul Kumar Sinha, Daniele Paliotta, Bálint Máté, Sebastian Pina-Otey, John A. Raine, Tobias Golling, François Fleuret:
SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics. CoRR abs/2202.05012 (2022) - [i10]Bálint Máté, Samuel Klein, Tobias Golling, François Fleuret:
Flowification: Everything is a Normalizing Flow. CoRR abs/2205.15209 (2022) - [i9]Samuel Klein, Tobias Golling:
Decorrelation with conditional normalizing flows. CoRR abs/2211.02486 (2022) - [i8]Samuel Klein, John Andrew Raine, Tobias Golling:
Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation. CoRR abs/2211.02487 (2022) - 2021
- [i7]Sabrina Amrouche, Moritz Kiehn, Tobias Golling, Andreas Salzburger:
Hashing and metric learning for charged particle tracking. CoRR abs/2101.06428 (2021) - [i6]Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather M. Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant:
The Tracking Machine Learning challenge : Throughput phase. CoRR abs/2105.01160 (2021) - [i5]Samuel Klein, John A. Raine, Sebastian Pina-Otey, Slava Voloshynovskiy, Tobias Golling:
Funnels: Exact maximum likelihood with dimensionality reduction. CoRR abs/2112.08069 (2021) - [i4]Mariia Drozdova, Vitaliy Kinakh, Guillaume Quétant, Tobias Golling, Slava Voloshynovskiy:
Generation of data on discontinuous manifolds via continuous stochastic non-invertible networks. CoRR abs/2112.09646 (2021) - [i3]Vitaliy Kinakh, Mariia Drozdova, Guillaume Quétant, Tobias Golling, Slava Voloshynovskiy:
Information-theoretic stochastic contrastive conditional GAN: InfoSCC-GAN. CoRR abs/2112.09653 (2021) - [i2]Guillaume Quétant, Mariia Drozdova, Vitaliy Kinakh, Tobias Golling, Slava Voloshynovskiy:
Turbo-Sim: a generalised generative model with a physical latent space. CoRR abs/2112.10629 (2021)
2010 – 2019
- 2019
- [c3]Sabrina Amrouche, Tobias Golling, Moritz Kiehn, Claudia Plant
, Andreas Salzburger:
Similarity hashing for charged particle tracking. IEEE BigData 2019: 1595-1600 - 2018
- [c2]Paolo Calafiura
, Steven Farrell, Heather M. Gray, Jean-Roch Vlimant, Vincenzo Innocente, Andreas Salzburger, Sabrina Amrouche, Tobias Golling, Moritz Kiehn, Victor Estrade, Cécile Germain, Isabelle Guyon, Ed Moyse, David Rousseau, Yetkin Yilmaz, Vladimir Vava Gligorov, Mikhail Hushchyn, Andrey Ustyuzhanin
:
TrackML: A High Energy Physics Particle Tracking Challenge. eScience 2018: 344 - [c1]Dalila Salamani, Stefan Gadatsch, Tobias Golling, Graeme Andrew Stewart, Aishik Ghosh
, David Rousseau, Ahmed Hasib, Jana Schaarschmidt:
Deep Generative Models for Fast Shower Simulation in ATLAS. eScience 2018: 348 - [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)
Coauthor Index

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last updated on 2023-03-24 23:52 CET by the dblp team
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