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Jean-Roch Vlimant
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2020 – today
- 2023
- [j11]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
The Tracking Machine Learning Challenge: Throughput Phase. Comput. Softw. Big Sci. 7(1): 1 (2023) - [i29]Farouk Mokhtar, Joosep Pata, Javier M. Duarte, Eric Wulff, Maurizio Pierini, Jean-Roch Vlimant:
Progress towards an improved particle flow algorithm at CMS with machine learning. CoRR abs/2303.17657 (2023) - [i28]Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant:
Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation. CoRR abs/2311.14160 (2023) - [i27]Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant:
Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder. CoRR abs/2311.17162 (2023) - 2022
- [j10]Eric A. Moreno
Source-agnostic gravitational-wave detection with recurrent autoencoders. Mach. Learn. Sci. Technol. 3(2): 25001 (2022) - [j9]Mary Touranakou
Particle-based fast jet simulation at the LHC with variational autoencoders. Mach. Learn. Sci. Technol. 3(3): 35003 (2022) - [d3]Mary Touranakou
Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders: generator-level and reconstruction-level jets dataset. Zenodo, 2022 - [i26]Joosep Pata, Javier M. Duarte, Farouk Mokhtar, Eric Wulff, Jieun Yoo, Jean-Roch Vlimant, Maurizio Pierini, Maria Girone:
Machine Learning for Particle Flow Reconstruction at CMS. CoRR abs/2203.00330 (2022) - [i25]Mary Touranakou, Nadezda Chernyavskaya, Javier M. Duarte, Dimitrios Gunopoulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant:
Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders. CoRR abs/2203.00520 (2022) - [i24]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
- [j8]Cheng Chen, Olmo Cerri, Thong Q. Nguyen, Jean-Roch Vlimant, Maurizio Pierini:
Analysis-Specific Fast Simulation at the LHC with Deep Learning. Comput. Softw. Big Sci. 5(1) (2021) - [j7]Wen Guan, Gabriel N. Perdue
Quantum machine learning in high energy physics. Mach. Learn. Sci. Technol. 2(1): 11003 (2021) - [j6]Jonathan Shlomi
Graph neural networks in particle physics. Mach. Learn. Sci. Technol. 2(2): 21001 (2021) - [j5]Cenk Tüysüz
Hybrid quantum classical graph neural networks for particle track reconstruction. Quantum Mach. Intell. 3(2): 1-20 (2021) - [j4]Alexander Zlokapa
Charged particle tracking with quantum annealing optimization. Quantum Mach. Intell. 3(2): 1-11 (2021) - [c4]Oceane Bel, Joosep Pata, Jean-Roch Vlimant, Nathan R. Tallent
Diolkos: improving ethernet throughput through dynamic port selection. CF 2021: 83-92 - [c3]Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos:
Particle Cloud Generation with Message Passing Generative Adversarial Networks. NeurIPS 2021: 23858-23871 - [i23]Joosep Pata, Javier M. Duarte
MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks. CoRR abs/2101.08578 (2021) - [i22]Xiangyang Ju
Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. CoRR abs/2103.06995 (2021) - [i21]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) - [i20]Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopoulos:
Particle Cloud Generation with Message Passing Generative Adversarial Networks. CoRR abs/2106.11535 (2021) - [i19]Eric A. Moreno, Jean-Roch Vlimant, Maria Spiropulu, Bartlomiej Borzyszkowski, Maurizio Pierini:
Source-Agnostic Gravitational-Wave Detection with Recurrent Autoencoders. CoRR abs/2107.12698 (2021) - [i18]Cenk Tüysüz, Carla Rieger, Kristiane Novotny, Bilge Demirköz, Daniel Dobos, Karolos Potamianos, Sofia Vallecorsa, Jean-Roch Vlimant, Richard Forster:
Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstruction. CoRR abs/2109.12636 (2021) - [i17]Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte
Applications and Techniques for Fast Machine Learning in Science. CoRR abs/2110.13041 (2021) - [i16]Farouk Mokhtar, Raghav Kansal, Daniel Diaz
Explaining machine-learned particle-flow reconstruction. CoRR abs/2111.12840 (2021) - [i15]Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance. CoRR abs/2111.12849 (2021) - 2020
- [i14]Oliver Knapp, Günther Dissertori, Olmo Cerri, Thong Q. Nguyen, Jean-Roch Vlimant, Maurizio Pierini:
Adversarially Learned Anomaly Detection on CMS Open Data: re-discovering the top quark. CoRR abs/2005.01598 (2020) - [i13]Nicholas Choma, Daniel Murnane, Xiangyang Ju, Paolo Calafiura, Sean Conlon, Steven Farrell, Prabhat, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Panagiotis Spentzouris, Jean-Roch Vlimant, Maria Spiropulu, Adam Aurisano
Track Seeding and Labelling with Embedded-space Graph Neural Networks. CoRR abs/2007.00149 (2020) - [i12]Cheng Chen, Olmo Cerri, Thong Q. Nguyen, Jean-Roch Vlimant, Maurizio Pierini:
Data Augmentation at the LHC through Analysis-specific Fast Simulation with Deep Learning. CoRR abs/2010.01835 (2020) - [i11]Raghav Kansal, Javier M. Duarte
Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics. CoRR abs/2012.00173 (2020) - [i10]Jean-Roch Vlimant, Junqi Yin:
Distributed Training and Optimization Of Neural Networks. CoRR abs/2012.01839 (2020)
2010 – 2019
- 2019
- [j3]Thong Q. Nguyen
Topology Classification with Deep Learning to Improve Real-Time Event Selection at the LHC. Comput. Softw. Big Sci. 3(1) (2019) - [i9]Alexander Zlokapa, Abhishek Anand, Jean-Roch Vlimant, Javier M. Duarte
Charged particle tracking with quantum annealing-inspired optimization. CoRR abs/1908.04475 (2019) - [i8]Alexander Zlokapa, Alex Mott, Joshua Job, Jean-Roch Vlimant, Daniel A. Lidar, Maria Spiropulu:
Quantum adiabatic machine learning with zooming. CoRR abs/1908.04480 (2019) - [i7]Dawit Belayneh, Federico Carminati, Amir Farbin, Benjamin Hooberman, Gulrukh Khattak, Miaoyuan Liu, Junze Liu, Dominick Olivito, Vitória Barin Pacela, Maurizio Pierini, Alexander G. Schwing, Maria Spiropulu, Sofia Vallecorsa, Jean-Roch Vlimant, Wei Wei, Matt Zhang:
Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics. CoRR abs/1912.06794 (2019) - 2018
- [c2]Paolo Calafiura
TrackML: A High Energy Physics Particle Tracking Challenge. eScience 2018: 344 - [d2]Andreas Salzburger
TrackML Throughput Phase. Zenodo, 2018 - [d1]Andreas Salzburger
TrackML Particle Tracking Challenge. Zenodo, 2018 - [i6]Thong Q. Nguyen
Topology classification with deep learning to improve real-time event selection at the LHC. CoRR abs/1807.00083 (2018) - [i5]Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano
Machine Learning in High Energy Physics Community White Paper. CoRR abs/1807.02876 (2018) - [i4]Jesus Arjona Martinez, Olmo Cerri, Maurizio Pierini, Maria Spiropulu, Jean-Roch Vlimant:
Pileup mitigation at the Large Hadron Collider with Graph Neural Networks. CoRR abs/1810.07988 (2018) - [i3]Olmo Cerri, Thong Q. Nguyen
Variational Autoencoders for New Physics Mining at the Large Hadron Collider. CoRR abs/1811.10276 (2018) - 2017
- [j2]Harvey B. Newman, Maria Spiropulu, Justas Balcas, Dorian Kcira, Iosif Legrand, Azher Mughal, Jean-Roch Vlimant, Ramiro Voicu:
Next-Generation Exascale Network Integrated Architecture for Global Science [Invited]. JOCN 9(2): A162-A169 (2017) - [j1]Alex Mott
Solving a Higgs optimization problem with quantum annealing for machine learning. Nat. 550(7676): 375-379 (2017) - [i2]V. Azzolini, Maxim Borisyak, Gianluca Cerminara, Denis Derkach, Giovanni Franzoni, F. De Guio, O. Koval, Maurizio Pierini, Adrian Alan Pol
Deep learning for inferring cause of data anomalies. CoRR abs/1711.07051 (2017) - [i1]Dustin Anderson, Jean-Roch Vlimant, Maria Spiropulu:
An MPI-Based Python Framework for Distributed Training with Keras. CoRR abs/1712.05878 (2017) - 2016
- [c1]Harvey B. Newman, Maria Spiropulu, Justas Balcas, Dorian Kcira, Iosif Legrand, Azher Mughal, Jean-Roch Vlimant, Ramiro Voicu:
SDN next generation integrated architecture for HEP and global science. OFC 2016: 1-3
Coauthor Index
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