| 2025 | GECCO | Evolutionary Reinforcement Learning. | Antoine Cully, Bryan Lim, Paul Templier, Manon Flageat |
| 2025 | GECCO | Extract-QD Framework: A Generic Approach for Quality-Diversity in Noisy, Stochastic or Uncertain Domains. | Manon Flageat, Johann Huber, Franois Hlnon, Stphane Doncieux, Antoine Cully |
| 2024 | AAAI | Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms. | Manon Flageat, Bryan Lim, Antoine Cully |
| 2024 | GECCO | Enhancing MAP-Elites with Multiple Parallel Evolution Strategies. | Manon Flageat, Bryan Lim, Antoine Cully |
| 2024 | GECCO | Evolutionary Reinforcement Learning. | Manon Flageat, Bryan Lim, Antoine Cully |
| 2023 | GECCO | MAP-Elites with Descriptor-Conditioned Gradients and Archive Distillation into a Single Policy. | Maxence Faldor, Flix Chalumeau, Manon Flageat, Antoine Cully |
| 2023 | GECCO | Benchmark Tasks for Quality-Diversity Applied to Uncertain Domains. | Manon Flageat, Luca Grillotti, Antoine Cully |
| 2023 | GECCO | Don't Bet on Luck Alone: Enhancing Behavioral Reproducibility of Quality-Diversity Solutions in Uncertain Domains. | Luca Grillotti, Manon Flageat, Bryan Lim, Antoine Cully |
| 2023 | GECCO | Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning. | Bryan Lim, Manon Flageat, Antoine Cully |
| 2020 | ESANN | Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control. | Manon Flageat, Kai Arulkumaran, Anil A. Bharath |