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Prune Responsibly

Sep 10, 2020
Michela Paganini


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Bespoke vs. PrĂȘt-Ă -Porter Lottery Tickets: Exploiting Mask Similarity for Trainable Sub-Network Finding

Jul 06, 2020
Michela Paganini, Jessica Zosa Forde

* arXiv admin note: text overlap with arXiv:2001.05050 

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dagger: A Python Framework for Reproducible Machine Learning Experiment Orchestration

Jun 12, 2020
Michela Paganini, Jessica Zosa Forde

* 4 pages, 3 code listings, 1 figure 

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Streamlining Tensor and Network Pruning in PyTorch

Apr 28, 2020
Michela Paganini, Jessica Forde

* 5 pages, 1 figure, 5 code listings. Published as a workshop paper at ICLR 2020 

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On Iterative Neural Network Pruning, Reinitialization, and the Similarity of Masks

Jan 14, 2020
Michela Paganini, Jessica Forde

* 8 pages, 8 figures, plus 5 appendices with additional figures and tables 

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One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers

Jun 06, 2019
Ari S. Morcos, Haonan Yu, Michela Paganini, Yuandong Tian


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The Scientific Method in the Science of Machine Learning

Apr 24, 2019
Jessica Zosa Forde, Michela Paganini

* 4 pages + 1 appendix. Presented at the ICLR 2019 Debugging Machine Learning Models workshop 

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Machine Learning Solutions for High Energy Physics: Applications to Electromagnetic Shower Generation, Flavor Tagging, and the Search for di-Higgs Production

Mar 12, 2019
Michela Paganini

* 413 pages, 10 chapters 

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Machine Learning in High Energy Physics Community White Paper

Jul 08, 2018
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 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 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, PrzemysƂaw KarpiƄski, 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 Neubauer, Harvey Newman, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel 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 Stewart, Bob Stienen, Ian Stockdale, Giles Strong, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Sofia Vallecorsa, Mauro Verzetti, Xavier VilasĂ­s-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Omar Zapata

* Editors: Sergei Gleyzer, Paul Seyfert and Steven Schramm 

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CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks

Dec 21, 2017
Michela Paganini, Luke de Oliveira, Benjamin Nachman

* Phys. Rev. D 97, 014021 (2018) 
* 14 pages, 4 tables, 13 figures; version accepted by Physical Review D (PRD) 

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Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeters

Dec 21, 2017
Michela Paganini, Luke de Oliveira, Benjamin Nachman

* Phys. Rev. Lett. 120, 042003 (2018) 
* 6 pages, 3 figures; version accepted by Physical Review Letters (PRL) 

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Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC

Nov 29, 2017
Wahid Bhimji, Steven Andrew Farrell, Thorsten Kurth, Michela Paganini, Prabhat, Evan Racah

* Presented at ACAT 2017 Conference, Submitted to J. Phys. Conf. Ser 

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Controlling Physical Attributes in GAN-Accelerated Simulation of Electromagnetic Calorimeters

Nov 23, 2017
Luke de Oliveira, Michela Paganini, Benjamin Nachman

* 7 pages, 5 figures, in proceedings of the 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2017) 

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Machine Learning Algorithms for $b$-Jet Tagging at the ATLAS Experiment

Nov 23, 2017
Michela Paganini

* 7 pages, 5 figures, in proceedings of the 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2017) 

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Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis

Jun 13, 2017
Luke de Oliveira, Michela Paganini, Benjamin Nachman

* Comput Softw Big Sci (2017) 1: 4 
* 23 pages, 23 figures, 1 table, and appendix; Added new validation metric, acknowledgements, minor corrections 

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