Jean-Roch Vlimant

Orcid: 0000-0002-9705-101X

According to our database¹, Jean-Roch Vlimant authored at least 43 papers between 2016 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2023

The Tracking Machine Learning Challenge: Throughput Phase.

[BibT_eX]

[DOI]

Comput. Softw. Big Sci., December, 2023

Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder.

[BibT_eX]

[DOI]

CoRR, 2023

Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation.

[BibT_eX]

[DOI]

CoRR, 2023

Progress towards an improved particle flow algorithm at CMS with machine learning.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders: generator-level and reconstruction-level jets dataset.

[BibT_eX]

[DOI]

Mary Touranakou

Nadezda Chernyavskaya

Dataset, February, 2022

Particle-based fast jet simulation at the LHC with variational autoencoders.

[BibT_eX]

[DOI]

Mary Touranakou

Nadezda Chernyavskaya

Mach. Learn. Sci. Technol., 2022

Source-agnostic gravitational-wave detection with recurrent autoencoders.

[BibT_eX]

[DOI]

Eric A. Moreno

Bartlomiej Borzyszkowski

Maurizio Pierini

Jean-Roch Vlimant

Maria Spiropulu

Mach. Learn. Sci. Technol., 2022

Data Science and Machine Learning in Education.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

Mary Touranakou

Nadezda Chernyavskaya

CoRR, 2022

Machine Learning for Particle Flow Reconstruction at CMS.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Charged particle tracking with quantum annealing optimization.

[BibT_eX]

[DOI]

Quantum Mach. Intell., 2021

Hybrid quantum classical graph neural networks for particle track reconstruction.

[BibT_eX]

[DOI]

Quantum Mach. Intell., 2021

Graph neural networks in particle physics.

[BibT_eX]

[DOI]

Jonathan Shlomi

Peter W. Battaglia

Jean-Roch Vlimant

Mach. Learn. Sci. Technol., 2021

Quantum machine learning in high energy physics.

[BibT_eX]

[DOI]

Mach. Learn. Sci. Technol., 2021

Analysis-Specific Fast Simulation at the LHC with Deep Learning.

[BibT_eX]

[DOI]

Comput. Softw. Big Sci., 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Explaining machine-learned particle-flow reconstruction.

[BibT_eX]

[DOI]

CoRR, 2021

Applications and Techniques for Fast Machine Learning in Science.

[BibT_eX]

[DOI]

Allison McCarn Deiana

Nhan Tran

Joshua Agar

Michaela Blott

Giuseppe Di Guglielmo

Tomás E. Müller-Bravo

Seyedramin Rasoulinezhad

Maria Domenica Galati

Mohammed Attia Mohammed

Subramanian Ramamoorthy

CoRR, 2021

Particle Cloud Generation with Message Passing Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2021

Physics and Computing Performance of the Exa.TrkX TrackML Pipeline.

[BibT_eX]

[DOI]

CoRR, 2021

MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks.

[BibT_eX]

[DOI]

CoRR, 2021

Particle Cloud Generation with Message Passing Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Diolkos: improving ethernet throughput through dynamic port selection.

[BibT_eX]

[DOI]

Proceedings of the CF '21: Computing Frontiers Conference, 2021

2020

Distributed Training and Optimization Of Neural Networks.

[BibT_eX]

[DOI]

Jean-Roch Vlimant

Junqi Yin

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

Data Augmentation at the LHC through Analysis-specific Fast Simulation with Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Track Seeding and Labelling with Embedded-space Graph Neural Networks.

[BibT_eX]

[DOI]

Panagiotis Spentzouris

CoRR, 2020

Adversarially Learned Anomaly Detection on CMS Open Data: re-discovering the top quark.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Topology Classification with Deep Learning to Improve Real-Time Event Selection at the LHC.

[BibT_eX]

[DOI]

Comput. Softw. Big Sci., December, 2019

Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics.

[BibT_eX]

[DOI]

CoRR, 2019

Quantum adiabatic machine learning with zooming.

[BibT_eX]

[DOI]

CoRR, 2019

Charged particle tracking with quantum annealing-inspired optimization.

[BibT_eX]

[DOI]

CoRR, 2019

2018

TrackML Throughput Phase.

[BibT_eX]

[DOI]

Dataset, September, 2018

TrackML Particle Tracking Challenge.

[BibT_eX]

[DOI]

Dataset, August, 2018

Variational Autoencoders for New Physics Mining at the Large Hadron Collider.

[BibT_eX]

[DOI]

CoRR, 2018

Pileup mitigation at the Large Hadron Collider with Graph Neural Networks.

[BibT_eX]

[DOI]

Jesus Arjona Martinez

CoRR, 2018

Machine Learning in High Energy Physics Community White Paper.

[BibT_eX]

[DOI]

Juan Pedro Araque Espinosa

Konstantin Kanishchev

Graeme Andrew Stewart

Xavier Vilasís-Cardona

CoRR, 2018

TrackML: A High Energy Physics Particle Tracking Challenge.

[BibT_eX]

[DOI]

Vladimir Vava Gligorov

Mikhail Hushchyn

Andrey Ustyuzhanin

Proceedings of the 14th IEEE International Conference on e-Science, 2018

2017

Solving a Higgs optimization problem with quantum annealing for machine learning.

[BibT_eX]

[DOI]

Nat., 2017

Next-Generation Exascale Network Integrated Architecture for Global Science [Invited].

[BibT_eX]

[DOI]

JOCN, 2017

An MPI-Based Python Framework for Distributed Training with Keras.

[BibT_eX]

[DOI]

Dustin Anderson

Jean-Roch Vlimant

Maria Spiropulu

CoRR, 2017

Deep learning for inferring cause of data anomalies.

[BibT_eX]

[DOI]

CoRR, 2017

2016

SDN next generation integrated architecture for HEP and global science.

[BibT_eX]

[DOI]

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2016

Jean-Roch Vlimant

Timeline

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