Photonic co-processors in HPC: Using LightOn OPUs for Randomized Numerical Linear Algebra. - Daniel Hesslow; Alessandro Cappelli; Igor Carron; Laurent Daudet; Raphaël Lafargue; Kilian Müller; Ruben Ohana; Gustave Pariente; Iacopo Poli (HCS, 2021)

EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. - Yassir Bendou; Yuqing Hu 001; Raphaël Lafargue; Giulia Lioi; Bastien Pasdeloup; Stéphane Pateux; Vincent Gripon (CoRR, 2022)

Easy - Ensemble Augmented-Shot-Y-Shaped Learning: State-of-the-Art Few-Shot Classification with Simple Components. - Yassir Bendou; Yuqing Hu 001; Raphaël Lafargue; Giulia Lioi; Bastien Pasdeloup; Stéphane Pateux; Vincent Gripon (J. Imaging, 2022)

Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes. - Raphaël Lafargue; Yassir Bendou; Bastien Pasdeloup; Jean-Philippe Diguet; Ian D. Reid 001; Vincent Gripon; Jack Valmadre (CoRR, 2024)

Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning. - Raphaël Lafargue; Luke Smith; Franck Vermet; Mathias Löwe; Ian D. Reid 001; Vincent Gripon; Jack Valmadre (CoRR, 2024)

Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning. - Raphaël Lafargue; Luke Smith; Franck Vermet; Matthias Löwe; Ian Reid 001; Jack Valmadre; Vincent Gripon (Trans. Mach. Learn. Res., 2024)

Few-shot learning, a data-centric approach for adaptation. (Approches centrées sur les données pour l'apprentissage parcimonieux). - Raphaël Lafargue (2024)