3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
Finetuning Offline World Models in the Real World
Yunhai Feng, Nicklas Hansen, Ziyan Xiong +2
Reinforcement Learning (RL) is notoriously data-inefficient, which makes training on a real robot difficult. While model-based RL algorithms (world models) improve data-efficiency…
cs.LG2022★ 3 cited
Graph Inverse Reinforcement Learning from Diverse Videos
Sateesh Kumar, Jonathan Zamora, Nicklas Hansen +2
Research on Inverse Reinforcement Learning (IRL) from third-person videos has shown encouraging results on removing the need for manual reward design for robotic tasks. However, mo…