Polynomial Data Compression for Large-Scale Physics Experiments. - Pierre Aubert; Thomas Vuillaume; Gilles Maurin; Jean Jacquemier; Giovanni Lamanna; Nahid Emad (Comput. Softw. Big Sci., 2018)

Indexed Operations for Non-rectangular Lattices Applied to Convolutional Neural Networks. - Mikaël Jacquemont; Luca Antiga; Thomas Vuillaume; Giorgia Silvestri; Alexandre Benoît; Patrick Lambert; Gilles Maurin (VISIGRAPP (5: VISAPP), 2019)

Deep Learning for Astrophysics, Understanding the Impact of Attention on Variability Induced by Parameter Initialization. - Mikaël Jacquemont; Thomas Vuillaume; Alexandre Benoît; Gilles Maurin; Patrick Lambert (ICPR Workshops (3), 2020)

First Full-Event Reconstruction from Imaging Atmospheric Cherenkov Telescope Real Data with Deep Learning. - Mikaël Jacquemont; Thomas Vuillaume; Alexandre Benoît; Gilles Maurin; Patrick Lambert; Giovanni Lamanna (CBMI, 2021)

Multi-Task Architecture with Attention for Imaging Atmospheric Cherenkov Telescope Data Analysis. - Mikaël Jacquemont; Thomas Vuillaume; Alexandre Benoît; Gilles Maurin; Patrick Lambert (VISIGRAPP (5: VISAPP), 2021)

Deep unsupervised domain adaptation applied to the Cherenkov Telescope Array Large-Sized Telescope. - Michaël Dell'aiera; Thomas Vuillaume; Mikaël Jacquemont; Alexandre Benoît (CBMI, 2023)