On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation. - Nicolas Brosse; Carlos Riquelme; Alice Martin 001; Sylvain Gelly; Eric Moulines (CoRR, 2020)

The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction. - Alice Martin 001; Charles Ollion; Florian Strub; Sylvain Le Corff; Olivier Pietquin (CoRR, 2020)

Learning Natural Language Generation from Scratch. - Alice Martin 001; Guillaume Quispe; Charles Ollion; Sylvain Le Corff; Florian Strub; Olivier Pietquin (CoRR, 2021)

Learning Natural Language Generation with Truncated Reinforcement Learning. - Alice Martin 001; Guillaume Quispe; Charles Ollion; Sylvain Le Corff; Florian Strub; Olivier Pietquin (NAACL-HLT, 2022)

Deep learning models and algorithms for sequential data problems: applications to language modelling and uncertainty quantification. (Modèles et algorithmes d'apprentissage profond pour de la donnée séquentielle: applications aux modèles de langage et à la quantification d'incertitude). - Alice Martin 001 (2022)

Backward Importance Sampling for Online Estimation of State Space Models. - Alice Martin 001; Marie-Pierre Étienne; Pierre Gloaguen; Sylvain Le Corff; Jimmy Olsson (J. Comput. Graph. Stat., 2023)