Recurrent networks, hidden states and beliefs in partially observable environments. - Gaspard Lambrechts; Adrien Bolland; Damien Ernst (Trans. Mach. Learn. Res., 2022)

Cracking the genetic code with neural networks. - Marc Joiret; Marine Leclercq; Gaspard Lambrechts; Francesca Rapino; Pierre Close; Gilles Louppe; Liesbet Geris (Frontiers Artif. Intell., 2023)

Warming up recurrent neural networks to maximise reachable multistability greatly improves learning. - Gaspard Lambrechts; Florent De Geeter; Nicolas Vecoven; Damien Ernst; Guillaume Drion (Neural Networks, 2023)

Informed POMDP: Leveraging Additional Information in Model-Based RL. - Gaspard Lambrechts; Adrien Bolland; Damien Ernst (RLJ, 2024)

Behind the Myth of Exploration in Policy Gradients. - Adrien Bolland; Gaspard Lambrechts; Damien Ernst (CoRR, 2024)

Reinforcement Learning to improve delta robot throws for sorting scrap metal. - Arthur Louette; Gaspard Lambrechts; Damien Ernst; Eric Pirard; Godefroid Dislaire (CoRR, 2024)

Parallelizing Autoregressive Generation with Variational State Space Models. - Gaspard Lambrechts; Yann Claes; Pierre Geurts; Damien Ernst (CoRR, 2024)

Off-Policy Maximum Entropy RL with Future State and Action Visitation Measures. - Adrien Bolland; Gaspard Lambrechts; Damien Ernst (CoRR, 2024)

A Theoretical Justification for Asymmetric Actor-Critic Algorithms. - Gaspard Lambrechts; Damien Ernst; Aditya Mahajan (CoRR, 2025)