Supaero Reinforcement Learning Initiative

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Internships in SuReLI

The Supaero Reinforcement Learning Initiative (SuReLI) can host internships this year over Spring and Summer. Those are generally open to outstanding MSc students, although we might be able to arrange things for PhD students too (with more flexible dates). Check our website and publications for our current research interests.

Among current hot topics:

Common application benchmarks in SuReLI:

We can offer detailed internship topics, but we are interested in particular in students who take an interest in our research first. We are also open to discussing new research topics. Feel free to reach out to Emmanuel Rachelson to discuss your research proposal. Some opportunities to stay in the team as a PhD student might arise during the coming year.

[1] Bertoin, D., & Rachelson, E. (2022). Disentanglement by cyclic reconstruction. IEEE Transactions on Neural Networks and Learning Systems.
[2] Bertoin, D., & Rachelson, E. (2022). Local Feature Swapping for Generalization in Reinforcement Learning. In International Conference on Learning Representations.
[3] Bertoin, D., Zouitine, A., Zouitine, M., & Rachelson, E. (2022). Look where you look! Saliency-guided Q-networks for visual RL tasks. In 36th Conference on Neural Information Processing Systems.
[4] Lahire, T., Geist, M., & Rachelson, E. (2022). Large Batch Experience Replay. In 39th International Conference on Machine Learning.
[5] Templier, P., Rachelson, E., & Wilson, D. G. (2021). A geometric encoding for neural network evolution. In Genetic and Evolutionary Computation Conference.
[6] Maile, K., Rachelson, E., Luga, H., & Wilson, D. G. (2022). When, where, and how to add new neurons to ANNs. In International Conference on Automated Machine Learning.