Learning Compositional Neural Programs with Recursive Tree Search and Planning. - Thomas Pierrot; Guillaume Ligner; Scott E. Reed; Olivier Sigaud; Nicolas Perrin 001; Alexandre Laterre; David Kas; Karim Beguir; Nando de Freitas (NeurIPS, 2019)

QD-RL: Efficient Mixing of Quality and Diversity in Reinforcement Learning. - Geoffrey Cideron; Thomas Pierrot; Nicolas Perrin 001; Karim Beguir; Olivier Sigaud (CoRR, 2020)

Learning Compositional Neural Programs for Continuous Control. - Thomas Pierrot; Nicolas Perrin 001; Feryal M. P. Behbahani; Alexandre Laterre; Olivier Sigaud; Karim Beguir; Nando de Freitas (CoRR, 2020)

Offline Reinforcement Learning Hands-On. - Louis Monier; Jakub Kmec; Alexandre Laterre; Thomas Pierrot; Valentin Courgeau; Olivier Sigaud; Karim Beguir (CoRR, 2020)

Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning. - Marcin J. Skwark; Nicolás López Carranza; Thomas Pierrot; Joe Phillips; Slim Said; Alexandre Laterre; Amine Kerkeni; Ugur Sahin; Karim Beguir (CoRR, 2020)

First-Order and Second-Order Variants of the Gradient Descent in a Unified Framework. - Thomas Pierrot; Nicolas Perrin-Gilbert; Olivier Sigaud (ICANN (2), 2021)

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)

Multi-objective quality diversity optimization. - Thomas Pierrot; Guillaume Richard; Karim Beguir; Antoine Cully (GECCO, 2022)

Fast Population-Based Reinforcement Learning on a Single Machine. - Arthur Flajolet; Claire Bizon Monroc; Karim Beguir; Thomas Pierrot (ICML, 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)

Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces. - Raphaël Boige; Guillaume Richard; Jérémie Donà; Thomas Pierrot; Antoine Cully (GECCO, 2023)

Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding Exploration. - Hannah Janmohamed; Thomas Pierrot; Antoine Cully (GECCO, 2023)

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)

Evolving Populations of Diverse RL Agents with MAP-Elites. - Thomas Pierrot; Arthur Flajolet (ICLR, 2023)

PASTA: Pretrained Action-State Transformer Agents. - Raphaël Boige; Yannis Flet-Berliac; Arthur Flajolet; Guillaume Richard; Thomas Pierrot (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; Arthur Flajolet; Thomas Pierrot; Antoine Cully (CoRR, 2023)

Early computational detection of potential high-risk SARS-CoV-2 variants. - Karim Beguir; Marcin J. Skwark; Yunguan Fu; Thomas Pierrot; Nicolás López Carranza; Alexandre Laterre; Ibtissem Kadri; Abir Korched; Anna U. Lowegard; Bonny Gaby Lui; Bianca Sänger; Yunpeng Liu; et al. (Comput. Biol. Medicine, 2023)

Multi-Objective Quality-Diversity for Crystal Structure Prediction. - Hannah Janmohamed; Marta Wolinska; Shikha Surana; Thomas Pierrot; Aron Walsh; Antoine Cully (GECCO, 2024)

BulkRNABert: Cancer prognosis from bulk RNA-seq based language models. - Maxence Gélard; Guillaume Richard; Thomas Pierrot; Paul-Henry Cournède (ML4H@NeurIPS, 2024)

Multi-modal Transfer Learning between Biological Foundation Models. - Juan Jose Garau-Luis; Patrick Bordes; Liam Gonzalez; Masa Roller; Bernardo P. de Almeida; Christopher Blum; Lorenz Hexemer; Stefan Laurent; Maren Lang; Thomas Pierrot; Guillaume Richard (NeurIPS, 2024)

PASTA: Pretrained Action-State Transformer Agents. - Raphaël Boige; Yannis Flet-Berliac; Lars C. P. M. Quaedvlieg; Arthur Flajolet; Guillaume Richard; Thomas Pierrot (RLJ, 2024)

Learning the Language of Protein Structure. - Benoit Gaujac; Jérémie Donà; Liviu Copoiu; Timothy Atkinson 003; Thomas Pierrot; Thomas D. Barrett (CoRR, 2024)

Multi-modal Transfer Learning between Biological Foundation Models. - Juan Jose Garau-Luis; Patrick Bordes; Liam Gonzalez; Masa Roller; Bernardo P. de Almeida; Lorenz Hexemer; Christopher Blum; Stefan Laurent; Jan Grzegorzewski; Maren Lang; Thomas Pierrot; Guillaume Richard (CoRR, 2024)

Preference-Conditioned Gradient Variations for Multi-Objective Quality-Diversity. - Hannah Janmohamed; Maxence Faldor; Thomas Pierrot; Antoine Cully (CoRR, 2024)

Simple Guidance Mechanisms for Discrete Diffusion Models. - Yair Schiff; Subham Sekhar Sahoo; Hao Phung; Guanghan Wang; Sam Boshar; Hugo Dalla-torre; Bernardo P. de Almeida; Alexander Rush; Thomas Pierrot; Volodymyr Kuleshov (CoRR, 2024)

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)

Simple Guidance Mechanisms for Discrete Diffusion Models. - Yair Schiff; Subham Sekhar Sahoo; Hao Phung; Guanghan Wang; Sam Boshar; Hugo Dalla-torre; Bernardo P. de Almeida; Alexander M. Rush; Thomas Pierrot; Volodymyr Kuleshov (ICLR, 2025)