"Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at ..."

Vincent-Pierre Berges et al. (2023)

> Home

Details and statistics

DOI: 10.1109/CVPR52729.2023.01323

access: closed

type: Conference or Workshop Paper

metadata version: 2023-08-29

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/cvpr/BergesSCGMBU23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/cvpr/BergesSCGMBU23
Vincent-Pierre Berges, Andrew Szot, Devendra Singh Chaplot, Aaron Gokaslan, Roozbeh Mottaghi, Dhruv Batra, Eric Undersander:
Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at 100k Steps-Per-Second. CVPR 2023: 13767-13777

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.