Core Deep Learning

Deep learning being now a key component of AD systems, it is important to get a better understanding of its inner workings, in particular the link between the specifics of the learning optimization and the key properties (performance, regularity, robustness, generalization) of the trained models.

Selected publications

  1. Yihong Xu, Victor Letzelter, Mickaël Chen, Éloi Zablocki, Matthieu Cord
    under review, 2025
  2. David Perera*, Victor Letzelter*, Théo Mariotte, Adrien Cortés, Mickael Chen, Slim Essid, Gaël Richard
    NeurIPS, 2024

  3. Jayneel Parekh, Pegah Khayatan, Mustafa Shukor, Alasdair Newson, Matthieu Cord
    NeurIPS, 2024

  4. Paul Couairon, Mustafa Shukor, Jean-Emmanuel Haugeard, Matthieu Cord, Nicolas Thome
    NeurIPS, 2024


  5. Bjoern Michele, Alexandre Boulch, Tuan-Hung Vu, Gilles Puy, Renaud Marlet, Nicolas Courty
    ECCV, 2024

  6. Nermin Samet, Cédric Rommel, David Picard, Eduardo Valle
    ECCV Workshop, 2024


  7. Victor Letzelter, David Perera, Cédric Rommel, Mathieu Fontaine, Slim Essid, Gaël Richard, Patrick Pérez
    ICML, 2024

  8. Nicolas Dufour, Victor Besnier, Vicky Kalogeiton, David Picard
    CVPR, 2024highlight

  9. Folco Bertini Baldassini, Mustafa Shukor, Matthieu Cord, Laure Soulier, Benjamin Piwowarski
    CVPR Workshop on Prompting in Vision, 2024
  10. Victor Letzelter, Mathieu Fontaine, Mickaël Chen, Patrick Pérez, Slim Essid, and Gaël Richard
    NeurIPS, 2023

  11. Léon Zheng, Gilles Puy, Elisa Riccietti, Patrick Pérez, Rémi Gribonval
    GRETSI, 2023

  12. Léon Zheng, Elisa Riccietti, Rémi Gribonval
    SIAM Journal on Mathematics of Data Science, 2023

  13. Léon Zheng, Gilles Puy, Elisa Riccietti, Patrick Pérez, Rémi Gribonval
    ICLR, 2023
  14. Simon Roburin, Yann de Mont-Marin, Andrei Bursuc, Renaud Marlet, Patrick Pérez, Mathieu Aubry
    Neurocomputing, 2022
  15. Himalaya Jain, Spyros Gidaris, Nikos Komodakis, Patrick Pérez, and Matthieu Cord
    ECCV, 2020