Jean-Roch Vlimant

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 44

Top Topics

Machine Learning

Anomaly Detection

Top Venues

Mach. Learn. Sci. Technol.

Comput. Softw. Big Sci.

Quantum Mach. Intell.

Publications

Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant
Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder. CoRR (2023)
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 (2023)
Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant
Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation. CoRR (2023)
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) (2023)
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 (2022)
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 (2022)
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 (2022)
Eric A. Moreno, Bartlomiej Borzyszkowski, Maurizio Pierini, Jean-Roch Vlimant, Maria Spiropulu
Source-agnostic gravitational-wave detection with recurrent autoencoders. Mach. Learn. Sci. Technol. 3 (2) (2022)
Mary Touranakou, Nadezda Chernyavskaya, Javier M. Duarte, Dimitrios Gunopulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant
Particle-based fast jet simulation at the LHC with variational autoencoders. Mach. Learn. Sci. Technol. 3 (3) (2022)
Eric A. Moreno, Jean-Roch Vlimant, Maria Spiropulu, Bartlomiej Borzyszkowski, Maurizio Pierini
Source-Agnostic Gravitational-Wave Detection with Recurrent Autoencoders. CoRR (2021)
Joosep Pata, Javier M. Duarte, Jean-Roch Vlimant, Maurizio Pierini, Maria Spiropulu
MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks. CoRR (2021)
Jonathan Shlomi, Peter W. Battaglia, Jean-Roch Vlimant
Graph neural networks in particle physics. Mach. Learn. Sci. Technol. 2 (2) (2021)
Farouk Mokhtar, Raghav Kansal, Daniel Diaz, Javier M. Duarte, Joosep Pata, Maurizio Pierini, Jean-Roch Vlimant
Explaining machine-learned particle-flow reconstruction. CoRR (2021)
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)
Xiangyang Ju, Daniel Murnane, Paolo Calafiura, Nicholas Choma, Sean Conlon, Steven Farrell, Yaoyuan Xu, Maria Spiropulu, Jean-Roch Vlimant, Adam Aurisano, Jeremy Hewes, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Markus Atkinson, Mark Neubauer, Gage DeZoort, Savannah Thais, Aditi Chauhan, Alex Schuy, Shih-Chieh Hsu, Alexandra Ballow, Alina Lazar
Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. CoRR (2021)
Wen Guan, Gabriel N. Perdue, Arthur Pesah, Maria Schuld, Koji Terashi, Sofia Vallecorsa, Jean-Roch Vlimant
Quantum machine learning in high energy physics. Mach. Learn. Sci. Technol. 2 (1) (2021)
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen 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
Applications and Techniques for Fast Machine Learning in Science. CoRR (2021)
Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather 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 (2021)
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. Quantum Mach. Intell. 3 (2) (2021)
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 (2021)
Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz, Javier M. Duarte, Sukanya Krishna, Farouk Mokhtar, Jean-Roch Vlimant, Maurizio Pierini
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance. CoRR (2021)
Alexander Zlokapa, Abhishek Anand, Jean-Roch Vlimant, Javier M. Duarte, Joshua Job, Daniel A. Lidar, Maria Spiropulu
Charged particle tracking with quantum annealing optimization. Quantum Mach. Intell. 3 (2) (2021)
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)
Oceane Bel, Joosep Pata, Jean-Roch Vlimant, Nathan R. Tallent, Justas Balcas, Maria Spiropulu
Diolkos: improving ethernet throughput through dynamic port selection. CF (2021)
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 (2021)
Jean-Roch Vlimant, Junqi Yin
Distributed Training and Optimization Of Neural Networks. CoRR (2020)
Raghav Kansal, Javier M. Duarte, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopoulos
Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics. CoRR (2020)
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 (2020)
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, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy L. Usher
Track Seeding and Labelling with Embedded-space Graph Neural Networks. CoRR (2020)
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 (2020)
Thong Q. Nguyen, Daniel Weitekamp III, Dustin Anderson, Roberto Castello, Olmo Cerri, Maurizio Pierini, Maria Spiropulu, Jean-Roch Vlimant
Topology Classification with Deep Learning to Improve Real-Time Event Selection at the LHC. Comput. Softw. Big Sci. 3 (1) (2019)
Alexander Zlokapa, Abhishek Anand, Jean-Roch Vlimant, Javier M. Duarte, Joshua Job, Daniel A. Lidar, Maria Spiropulu
Charged particle tracking with quantum annealing-inspired optimization. CoRR (2019)
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 (2019)
Alexander Zlokapa, Alex Mott, Joshua Job, Jean-Roch Vlimant, Daniel A. Lidar, Maria Spiropulu
Quantum adiabatic machine learning with zooming. CoRR (2019)
Thong Q. Nguyen, Daniel Weitekamp III, Dustin Anderson, Roberto Castello, Olmo Cerri, Maurizio Pierini, Maria Spiropulu, Jean-Roch Vlimant
Topology classification with deep learning to improve real-time event selection at the LHC. CoRR (2018)
Paolo Calafiura, Steven Farrell, Heather 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)
Jesus Arjona Martinez, Olmo Cerri, Maurizio Pierini, Maria Spiropulu, Jean-Roch Vlimant
Pileup mitigation at the Large Hadron Collider with Graph Neural Networks. CoRR (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 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 Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Alexander 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 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 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 (2018)
Olmo Cerri, Thong Q. Nguyen, Maurizio Pierini, Maria Spiropulu, Jean-Roch Vlimant
Variational Autoencoders for New Physics Mining at the Large Hadron Collider. CoRR (2018)
Dustin Anderson, Jean-Roch Vlimant, Maria Spiropulu
An MPI-Based Python Framework for Distributed Training with Keras. CoRR (2017)
V. Azzolini, Maxim Borisyak, Gianluca Cerminara, Denis Derkach, Giovanni Franzoni, F. De Guio, O. Koval, Maurizio Pierini, Adrian Alan Pol, Fedor Ratnikov, Filip Siroky, Andrey Ustyuzhanin, Jean-Roch Vlimant
Deep learning for inferring cause of data anomalies. CoRR (2017)
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) (2017)
Alex Mott, Joshua Job, Jean-Roch Vlimant, Daniel A. Lidar, Maria Spiropulu
Solving a Higgs optimization problem with quantum annealing for machine learning. Nat. 550 (7676) (2017)
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)