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Julian Gao

2 accepted papers

2018

Neural Task Programming: Learning to Generalize Across Hierarchical Tasks

ICRA 2018poster

In this work, we propose a novel robot learning framework called Neural Task Programming (NTP), which bridges the idea of few-shot learning from demonstration and neural program induction. NTP takes as input a task specification (e.g., video demonstration of a task) and recursively decomposes it int…

Cited by 257SourcecodeScholar
2018

ROBOTURK: A Crowdsourcing Platform for Robotic Skill Learning through Imitation

CoRL 2018

Imitation Learning has empowered recent advances in learning robotic manipulation tasks by addressing shortcomings of Reinforcement Learning such as exploration and reward specification. However, research in this area has been limited to modest-sized datasets due to the difficulty of collecting larg

Cited by 0SourcePDFScholar