96 citations · 183 across the 10 of their papers we have counts for
3 papers · 1 filter
Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at 100k Steps-Per-Second
Vincent-Pierre Berges, Andrew Szot, Devendra Singh Chaplot +4
We present Galactic, a large-scale simulation and reinforcement-learning (RL) framework for robotic mobile manipulation in indoor environments. Specifically, a Fetch robot (equippe…
Habitat 2.0: Training Home Assistants to Rearrange their Habitat
Andrew Szot, Alex Clegg, Eric Undersander +18
We introduce Habitat 2.0 (H2.0), a simulation platform for training virtual robots in interactive 3D environments and complex physics-enabled scenarios. We make comprehensive contr…
Block-Sparse Recurrent Neural Networks
Sharan Narang, Eric Undersander, Gregory Diamos
Recurrent Neural Networks (RNNs) are used in state-of-the-art models in domains such as speech recognition, machine translation, and language modelling. Sparsity is a technique to…