1 citations · 1 across the 4 of their papers we have counts for
4 papers
Semantic World Models
Jacob Berg, Chuning Zhu, Yanda Bao +2
Planning with world models offers a powerful paradigm for robotic control. Conventional approaches train a model to predict future frames conditioned on current frames and actions,…
STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
Marius Memmel, Jacob Berg, Bingqing Chen +2
Robot learning is witnessing a significant increase in the size, diversity, and complexity of pre-collected datasets, mirroring trends in domains such as natural language processin…
Rank2Reward: Learning Shaped Reward Functions from Passive Video
Daniel Yang, Davin Tjia, Jacob Berg +3
Teaching robots novel skills with demonstrations via human-in-the-loop data collection techniques like kinesthetic teaching or teleoperation puts a heavy burden on human supervisor…
SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning
Jianlan Luo, Zheyuan Hu, Charles Xu +7
In recent years, significant progress has been made in the field of robotic reinforcement learning (RL), enabling methods that handle complex image observations, train in the real…