Monter d'un niveau |
Azambuja, R. , Fouad, H., Bouteiller, Y., Sol, C., & Beltrame, G. (mai 2022). When being soft makes you tough: a collision-resilient quadcopter inspired by arthropods' exoskeletons [Communication écrite]. IEEE International Conference on Robotics and Automation (ICRA 2022), Philadelphia, PA, USA. Lien externe
Bouteiller, Y. (2022). Managing the World Complexity: From Linear Regression to Deep Learning. Dans Foundations of Robotics: A Multidisciplinary Approach with Python and ROS (441-472). Lien externe
Bouteiller, Y. (2021). Deep Reinforcement Learning in Real-Time Environments [Mémoire de maîtrise, Polytechnique Montréal]. Disponible
Bouteiller, Y., Ramstedt, S., Beltrame, G., Pal, C. J., & Binas, J. (mai 2021). Reinforcement Learning with Random Delays [Affiche]. 9th International Conference on Learning Representations (ICLR 2021). Non disponible
Sperling, M., Bouteiller, Y., De Azambuja, R., & Beltrame, G. (mai 2020). Domain Generalization via Optical Flow: Training a CNN in a Low-Quality Simulation to Detect Obstacles in the Real World [Communication écrite]. 17th Conference on Computer and Robot Vision (CRV 2020), Ottawa, ON. Lien externe
Valenchon, N., Bouteiller, Y., Jourde, H. R., L'Heureux, X., Sobral, M., Coffey, E. B. J., & Beltrame, G. (2022). The Portiloop: A deep learning-based open science tool for closed-loop brain stimulation. PLOS ONE, 17(8), e0270696 (20 pages). Lien externe