On the Use of Dependencies in Relation Classification of Text with Deep Learning. - Bernard Espinasse; Sébastien Fournier; Adrian-Gabriel Chifu; Gaël Guibon; René Azcurra; Valentin Macé (CICLing (2), 2019)

Using Whole Document Context in Neural Machine Translation. - Valentin Macé; Christophe Servan (IWSLT, 2019)

Diversity policy gradient for sample efficient quality-diversity optimization. - Thomas Pierrot; Valentin Macé; Félix Chalumeau; Arthur Flajolet; Geoffrey Cideron; Karim Beguir; Antoine Cully; Olivier Sigaud; Nicolas Perrin-Gilbert (GECCO, 2022)

Assessing Quality-Diversity Neuro-Evolution Algorithms Performance in Hard Exploration Problems. - Félix Chalumeau; Thomas Pierrot; Valentin Macé; Arthur Flajolet; Karim Beguir; Antoine Cully; Nicolas Perrin-Gilbert (CoRR, 2022)

The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision Transformers. - Valentin Macé; Raphaël Boige; Félix Chalumeau; Thomas Pierrot; Guillaume Richard; Nicolas Perrin-Gilbert (GECCO, 2023)

Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery. - Félix Chalumeau; Raphaël Boige; Bryan Lim; Valentin Macé; Maxime Allard; Arthur Flajolet; Antoine Cully; Thomas Pierrot (ICLR, 2023)

QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration. - Félix Chalumeau; Bryan Lim; Raphaël Boige; Maxime Allard; Luca Grillotti; Manon Flageat; Valentin Macé; Arthur Flajolet; Thomas Pierrot; Antoine Cully (CoRR, 2023)

QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration. - Félix Chalumeau; Bryan Lim; Raphaël Boige; Maxime Allard; Luca Grillotti; Manon Flageat; Valentin Macé; Guillaume Richard; Arthur Flajolet; Thomas Pierrot; Antoine Cully (J. Mach. Learn. Res., 2024)

Diversity based exploration for deep reinforcement learning. (Exploration fondée sur la diversité pour l'apprentissage par renforcement profond). - Valentin Macé (2024)