Thomas Vuillaume
- Laboratoire d'Annecy de Physique des Particules (LAPP)
- Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])
Présentation
Hi. I am Thomas Vuillaume, a data scientist and research software engineer working at LAPP, CNRS.
I specialise in data analysis, IA and machine learning and (open) research software development.
https://vuillaut.github.io/
Publications
Publications
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The new architecture design of the Science Alert Generation pipeline of the Cherenkov Telescope Array Observatory39th International Cosmic Ray Conference, Jul 2025, Geneva, Switzerland. pp.597, ⟨10.22323/1.501.0597⟩ |
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SAG-SCI: the Real-time, High-level Analysis Software for Array Control and Data Acquisition of the Cherenkov Telescope Array Observatory39th International Cosmic Ray Conference, Jul 2025, Geneva, Switzerland. pp.794, ⟨10.22323/1.501.0794⟩ |
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Advanced stereoscopy applied to CTAO39th International Cosmic Ray Conference, Jul 2025, Geneva, Switzerland. pp.549, ⟨10.22323/1.501.0549⟩ |
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The first release of the Cherenkov Telescope Array Observatory array control and data acquisition softwareSPIE Astronomical Telescopes + Instrumentation 2024, Jul 2024, Montréal, Canada. pp.131011D, ⟨10.1117/12.3017568⟩ |
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To clean or not to clean? Influence of pixel removal on event reconstruction using deep learning in CTAO34th annual conference on Astronomical Data Analysis Software and Systems, Nov 2024, Valletta, Malta |
The science alert generation system of the Cherenkov Telescope Array ObservatorySPIE Astronomical Telescopes + Instrumentation 2024, Jun 2024, Yokohama, Japan. pp.1310129, ⟨10.1117/12.3017825⟩ |
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Methodology for the integration of the array control and data acquisition system with array elements of the Cherenkov Telescope Array ObservatorySPIE Astronomical Telescopes + Instrumentation 2024, Jul 2022, Montréal, Canada. pp.131010H, ⟨10.1117/12.3017493⟩ |
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The Real Time Analysis framework of the Cherenkov Telescope Array's Large-Sized Telescope38th International Cosmic Ray Conference, Jul 2023, Nagoya, Japan. pp.616, ⟨10.22323/1.444.0616⟩ |
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Deep unsupervised domain adaptation applied to the Cherenkov Telescope Array Large-Sized Telescope20th International Conference on Content-based Multimedia Indexing (CBMI 2023), Sep 2023, Orleans, France. pp.133-139, ⟨10.1145/3617233.3617279⟩ |
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Performance of the Large-Sized Telescope prototype of the Cherenkov Telescope Array38th International Cosmic Ray Conference, Jul 2023, Nagoya, Japan. pp.594, ⟨10.22323/1.444.0594⟩ |
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The lstMCpipe library32th Astronomical Data Analysis Software and Systems, Oct 2022, Online, Canada |
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lstchain: An Analysis Pipeline for LST-1, the First Prototype Large-Sized Telescope of CTA30th Astronomical Data Analysis Software and Systems, Nov 2020, Granada, Spain. pp.357 |
Single Imaging Atmospheric Cherenkov Telescope Full-Event Reconstruction with a Deep Multi-Task Learning Architecture30th Astronomical Data Analysis Software and Systems, Nov 2020, Granada, Spain. pp.203 |
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Camera Calibration of the CTA-LST prototype37th International Cosmic Ray Conference, Jul 2021, Berlin, Germany. pp.720, ⟨10.22323/1.395.0720⟩ |
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Analysis of the Cherenkov Telescope Array first Large-Sized Telescope real data using convolutional neural networks37th International Cosmic Ray Conference, Jul 2021, Berlin, Germany. pp.703, ⟨10.22323/1.395.0703⟩ |
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First Full-Event Reconstruction from Imaging Atmospheric Cherenkov Telescope Real Data with Deep LearningInternational Conference on Content-Based Multimedia Indexing (CBMI), Jun 2021, Lille, France. 6 p., ⟨10.1109/CBMI50038.2021.9461918⟩ |
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Monte Carlo Studies of Combined MAGIC and LST1 Observations36th International Cosmic Ray Conference, Jul 2019, Madison, United States. pp.659, ⟨10.22323/1.358.0659⟩ |
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The Cherenkov Telescope Array Performance in Divergent Mode36th International Cosmic Ray Conference, Jul 2019, Madison, United States. pp.664, ⟨10.22323/1.358.0664⟩ |
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Multi-Task Architecture with Attention for Imaging Atmospheric Cherenkov Telescope Data Analysis16th International Conference on ComputerVision Theory and Applications (VISAPP 2021), Feb 2021, online, France |
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The Science Alert Generation system of the Cherenkov Telescope Array Observatory37th International Cosmic Ray Conference, Jul 2021, Berlin, Germany. pp.937, ⟨10.22323/1.395.0937⟩ |
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Studying deep convolutional neural networks with hexagonal lattices for imaging atmospheric Cherenkov telescope event reconstruction36th International Cosmic Ray Conference, Jul 2019, Madison, United States. pp.753, ⟨10.22323/1.358.0753⟩ |
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Deep-learning-driven event reconstruction applied to simulated data from a single Large-Sized Telescope of CTA37th International Cosmic Ray Conference, Jul 2021, Berlin, Germany. pp.771, ⟨10.22323/1.395.0771⟩ |
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First follow-up of transient events with the CTA Large Size Telescope prototype37th International Cosmic Ray Conference, Jul 2021, Berlin, Germany. pp.838, ⟨10.22323/1.395.0838⟩ |
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Deep Learning for Astrophysics, Understanding the Impact of Attention on Variability Induced by Parameter InitializationICPR'2020 Workshop Explainable Deep Learning-AI, Jan 2021, Milan (on line), Italy |
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Physics Performance of the Large-Sized Telescope prototype of the Cherenkov Telescope Array37th International Cosmic Ray Conference, Jul 2021, Berlin, Germany |
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Single Imaging Atmospheric Cherenkov Telescope Full-Event Reconstruction with a Deep Multi-Task Learning ArchitectureAstronomical Data Analysis Software and Systems ADASS XXX, Nov 2020, Granada, Spain |
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Indexed Operations for Non-rectangular Lattices Applied to Convolutional Neural NetworksVISAPP, 14th International Conference on Computer Vision Theory and Applications, Feb 2019, Prague, Czech Republic |
Application of High Performance Computing and Vectorisation Solutions to Data Analysis for Imaging Atmospheric Cherenkov Telescopes26th Annual Astronomical Data Analysis Software and Systems Conference, Oct 2016, Trieste, Italy. pp.632 |
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GammaLearn - first steps to apply Deep Learning to the Cherenkov Telescope Array data23rd International Conference on Computing in High Energy and Nuclear Physics, Jul 2018, Sofia, Bulgaria. pp.06020, ⟨10.1051/epjconf/201921406020⟩ |
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GammaLearn: a Deep Learning framework for IACT data36th International Cosmic Ray Conference, Jul 2019, Madison, United States. pp.705 |
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Gammapy - A prototype for the CTA science toolsICRC 2017 - 35th International Cosmic Ray Conference, Jul 2017, Busan, South Korea. pp.766, ⟨10.22323/1.301.0766⟩ |
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A inhomogenous jet model for the broad band emission of radio loud AGNs35th International Cosmic Ray Conference, Jul 2017, Busan, South Korea. pp.864, ⟨10.22323/1.301.0864⟩ |
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High Performance Computing algorithms for Atmospheric Cherenkov Telescopes35th International Cosmic Ray Conference, Jul 2017, Busan, South Korea. pp.771, ⟨10.22323/1.301.0771⟩ |
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$ps^2chitt!$ – A Python package for the modelling of atmoSpheric Showers and CHerenkov Imaging Terrestrial Telescopes35th International Cosmic Ray Conference, Jul 2017, Busan, South Korea. pp.772, ⟨10.22323/1.301.0772⟩ |
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GammaLearn - first steps to apply Deep Learning to the Cherenkov Telescope Array data23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018), Jul 2018, Sofia, Bulgaria |
High Performance Computing algorithms for Atmospheric Cherenkov TelescopesThe 35th International Cosmic Ray Conference, the Astroparticle Physics Conference, Jul 2017, Bexco Busan, South Korea |
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The Real Time Analysis framework of the Cherenkov Telescope Array's Large-Sized TelescopeICRC 2023, Jul 2023, Nagoya, Japan |
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Science with the Cherenkov Telescope ArrayWORLD SCIENTIFIC, 2019, 9789813270091. ⟨10.1142/10986⟩ |
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Stereograph: Stereoscopic event reconstruction using graph neural networks applied to CTAO2025 |
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Deep Learning and IACT: Bridging the gap between Monte-Carlo simulations and LST-1 data using domain adaptation2024 |
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The eOSSR library2022 |
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H.E.S.S. first public test data release2018 |
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Modélisation de l'émission des noyaux actifs de galaxie à l'ère FermiAstrophysique [astro-ph]. Université Grenoble Alpes, 2015. Français. ⟨NNT : 2015GREAY089⟩ |
lstmcpipeLogiciel hal-04903552v1 |
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Gammapy Release V0.19Logiciel hal-03663345v1 |
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A Python Package for Gamma-ray AstronomyLogiciel hal-03713410v1 |
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Gammapy V1.0Logiciel hal-03885031v1 |