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On the Evaluation of Generative Models in High Energy Physics


Nov 18, 2022
Raghav Kansal, Anni Li, Javier Duarte, Nadezda Chernyavskaya, Maurizio Pierini, Breno Orzari, Thiago Tomei

* 11 pages, 5 figures, 3 tables, and a 3 page appenidx 

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Do graph neural networks learn traditional jet substructure?


Nov 17, 2022
Farouk Mokhtar, Raghav Kansal, Javier Duarte

* 5 pages, 4 figures. Accepted to Machine Learning for Physical Sciences NeurIPS 2022 workshop 

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Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders


Mar 01, 2022
Mary Touranakou, Nadezda Chernyavskaya, Javier Duarte, Dimitrios Gunopulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant

* 11 pages, 8 figures 

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Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance


Nov 24, 2021
Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz, Javier Duarte, Sukanya Krishna, Farouk Mokhtar, Jean-Roch Vlimant, Maurizio Pierini

* 5 pages, 2 figures. Accepted to the Machine Learning for the Physical Sciences workshop at NeurIPS 2021. arXiv admin note: text overlap with arXiv:2101.08320 

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Explaining machine-learned particle-flow reconstruction


Nov 24, 2021
Farouk Mokhtar, Raghav Kansal, Daniel Diaz, Javier Duarte, Joosep Pata, Maurizio Pierini, Jean-Roch Vlimant

* 5 pages, 3 figures. Accepted to Machine Learning for Physical Sciences NeurIPS 2021 workshop 

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Applications and Techniques for Fast Machine Learning in Science


Oct 25, 2021
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bahr, Jurgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomas E. Muller Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng

* 66 pages, 13 figures, 5 tables 

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A FAIR and AI-ready Higgs Boson Decay Dataset


Aug 04, 2021
Yifan Chen, E. A. Huerta, Javier Duarte, Philip Harris, Daniel S. Katz, Mark S. Neubauer, Daniel Diaz, Farouk Mokhtar, Raghav Kansal, Sang Eon Park, Volodymyr V. Kindratenko, Zhizhen Zhao, Roger Rusack

* 14 pages, 3 figures. Learn about the FAIR4HEP project at https://fair4hep.github.io 

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Particle Cloud Generation with Message Passing Generative Adversarial Networks


Jun 22, 2021
Raghav Kansal, Javier Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos

* 13 pages, 4 figures, 2 tables, and a 3 page appendix 

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Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics


Dec 08, 2020
Raghav Kansal, Javier Duarte, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopoulos

* 9 pages, 4 figures, 4 tables, To appear in Third Workshop on Machine Learning and the Physical Sciences (NeurIPS 2020) 

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