160 citations · 168 across the 8 of their papers we have counts for
8 papers
LeRobot: An Open-Source Library for End-to-End Robot Learning
Remi Cadene, Simon Aliberts, Francesco Capuano +14
Robotics is undergoing a significant transformation powered by advances in high-level control techniques based on machine learning, giving rise to the field of robot learning. Rece…
Robot Learning: A Tutorial
Francesco Capuano, Caroline Pascal, Adil Zouitine +2
Robot learning is at an inflection point, driven by rapid advancements in machine learning and the growing availability of large-scale robotics data. This shift from classical, mod…
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
Mustafa Shukor, Dana Aubakirova, Francesco Capuano +11
Vision-language models (VLMs) pretrained on large-scale multimodal datasets encode rich visual and linguistic knowledge, making them a strong foundation for robotics. Rather than t…
Solving robust MDPs as a sequence of static RL problems
Adil Zouitine, Matthieu Geist, Emmanuel Rachelson
Designing control policies whose performance level is guaranteed to remain above a given threshold in a span of environments is a critical feature for the adoption of reinforcement…
RRLS : Robust Reinforcement Learning Suite
Adil Zouitine, David Bertoin, Pierre Clavier +2
Robust reinforcement learning is the problem of learning control policies that provide optimal worst-case performance against a span of adversarial environments. It is a crucial in…
Time-Constrained Robust MDPs
Adil Zouitine, David Bertoin, Pierre Clavier +2
Robust reinforcement learning is essential for deploying reinforcement learning algorithms in real-world scenarios where environmental uncertainty predominates. Traditional robust…
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning
David Bertoin, Adil Zouitine, Mehdi Zouitine +1
Deep reinforcement learning policies, despite their outstanding efficiency in simulated visual control tasks, have shown disappointing ability to generalize across disturbances in…
River: machine learning for streaming data in Python
Jacob Montiel, Max Halford, Saulo Martiello Mastelini +8
River is a machine learning library for dynamic data streams and continual learning. It provides multiple state-of-the-art learning methods, data generators/transformers, performan…