Théo Vincent

Théo Vincent joined the Intelligent Autonomous Systems Group as a Ph.D. student in December 2022. He is part of the group SAIROL, a DFKI unit, and works under the supervision of Jan Peters. He is currently working on sample-efficient deep reinforcement learning methods. Théo published in top ML conferences, developing advanced algorithms for hyperparameter tuning (AdaQN), for discovering sparse neural network structures (EauDeQN), and for boosting the performance of classical RL algorithms (iS-QN, i-QN, and PBO).

During his studies, Théo focused on computer vision and reinforcement learning. He graduated from MVA, a double master's degree program in collaboration with ENS ParisSaclay and Ponts ParisTech. He did his master's thesis at IAS on value-based methods in offline settings supervised by Carlo D’Eramo.

Before his Ph.D., Théo worked in a Parisian lab called Saint-Venant lab, supervised by Rémi Carmigniani to track professional swimmers on video clips using Deep Learning. He then joined Signality, a Swedish start-up led by Mikael Rousson, to investigate the problem of finding a homography linking a football pitch to a camera. He also worked in the group of Chirag Patel at Harvard Medical School to understand how our organs are aging.

Publications

1. •     Bib
     Vincent, T.; Tripathi, Y.; Faust, T.; Oren, Y.; Peters, J.; D'Eramo, C. (2025). Bridging the Performance Gap Between Target-Free and Target-Based Reinforcement Learning With Iterated Q-Learning, European Workshop on Reinforcement Learning (EWRL).
2. •     Bib
     Vincent, T.; Faust, T.; Tripathi, Y.; Peters, J.; D'Eramo, C. (2025). Eau De Q-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning, Reinforcement Learning Journal (RLJ).
3. •     Bib
     Vincent, T.; Palenicek, D.; Belousov, B.; Peters, J.; D'Eramo, C. (2025). Iterated Q-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning, Transactions on Machine Learning Research (TMLR).
4. •     Bib
     Vincent, T.; Wahren, F.; Peters, J.; Belousov, B.; D'Eramo, C. (2025). Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning, International Conference on Learning Representations (ICLR).
5. •     Bib
     Vincent, T.; Metelli, A.; Belousov, B.; Peters, J.; Restelli, M.; D'Eramo, C. (2024). Parameterized Projected Bellman Operator, Proceedings of the National Conference on Artificial Intelligence (AAAI).