2 papers
cs.LG2022
Embodied vision for learning object representations
Arthur Aubret, Céline Teulière, Jochen Triesch
Recent time-contrastive learning approaches manage to learn invariant object representations without supervision. This is achieved by mapping successive views of an object onto clo…
cs.LG2021
DisTop: Discovering a Topological representation to learn diverse and rewarding skills
Arthur Aubret, Laetitia matignon, Salima Hassas
The optimal way for a deep reinforcement learning (DRL) agent to explore is to learn a set of skills that achieves a uniform distribution of states. Following this,we introduce Dis…