23 citations · 23 across the 3 of their papers we have counts for
3 papers
Disentangled Representation Learning through Unsupervised Symmetry Group Discovery
Barthélémy Dang-Nhu, Louis Annabi, Sylvain Argentieri
Symmetry-based disentangled representation learning leverages the group structure of environment transformations to uncover the latent factors of variation. Prior approaches to sym…
Learning agent's spatial configuration from sensorimotor invariants
Alban Laflaquière, J. Kevin O'Regan, Sylvain Argentieri +2
The design of robotic systems is largely dictated by our purely human intuition about how we perceive the world. This intuition has been proven incorrect with regard to a number of…
A Non-linear Approach to Space Dimension Perception by a Naive Agent
Alban Laflaquière, Sylvain Argentieri, Olivia Breysse +2
Developmental Robotics offers a new approach to numerous AI features that are often taken as granted. Traditionally, perception is supposed to be an inherent capacity of the agent.…