Information processing in large-scale cerebral networks: the causal connectivity approach. - Josette Pastor; Marc Lafon; Louise Travé-Massuyès; Jean-François Démonet; Bernard Doyon; Pierre Celsis (Biol. Cybern., 2000)

Modélisation de la propagation de l'information cérébrale par graphes causaux qualitatifs. (Modelisation of cerebral information propagation in causal qualitative networks). - Marc Lafon (2000)

Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection. - Marc Lafon; Elias Ramzi; Clément Rambour; Nicolas Thome (ICML, 2023)

GalLoP: Learning Global and Local Prompts for Vision-Language Models. - Marc Lafon; Elias Ramzi; Clément Rambour; Nicolas Audebert; Nicolas Thome (ECCV (61), 2024)

Supra-Laplacian Encoding for Transformer on Dynamic Graphs. - Yannis Karmim; Marc Lafon; Raphaël Fournier-S'niehotta; Nicolas Thome (NeurIPS, 2024)

Energy Correction Model in the Feature Space for Out-of-Distribution Detection. - Marc Lafon; Clément Rambour; Nicolas Thome (CoRR, 2024)

Understanding the Double Descent Phenomenon in Deep Learning. - Marc Lafon; Alexandre Thomas (CoRR, 2024)

ViLU: Learning Vision-Language Uncertainties for Failure Prediction. - Marc Lafon; Yannis Karmim; Julio Silva-Rodríguez; Paul Couairon; Clément Rambour; Raphaël Fournier-S'niehotta; Ismail Ben Ayed; Jose Dolz; Nicolas Thome (CoRR, 2025)

CLIPTTA: Robust Contrastive Vision-Language Test-Time Adaptation. - Marc Lafon; Gustavo Adolfo Vargas Hakim; Clément Rambour; Christian Desrosiers; Nicolas Thome (CoRR, 2025)